librarian-bots/dataset_cards_with_metadata

datasetId stringlengths 5 121	author stringlengths 2 42	last_modified unknown	likes int64 0 7.59k	tags sequencelengths 1 7.92k	task_categories sequencelengths 0 47 ⌀	createdAt unknown	card stringlengths 15 1.02M
tuandunghcmut/sp_bilingual_ds	tuandunghcmut	"2024-09-04T09:59:04Z"	0	[ "size_categories:1M<n<10M", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-09-04T08:33:31Z"	--- dataset_info: features: - name: image_name dtype: string - name: person_id dtype: int64 - name: caption_0 dtype: string - name: caption_1 dtype: string - name: attributes dtype: string - name: prompt_caption dtype: string - name: image dtype: image - name: viet_captions sequence: string - name: viet_prompt_caption sequence: string splits: - name: train num_bytes: 54940531595.615 num_examples: 4791127 download_size: 51005008832 dataset_size: 54940531595.615 configs: - config_name: default data_files: - split: train path: data/train-* ---
QuanHoangNgoc/EVJ_NonCluster	QuanHoangNgoc	"2024-10-22T04:18:28Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-10-22T04:12:29Z"	--- dataset_info: features: - name: answer dtype: string - name: image dtype: image - name: prompt dtype: string splits: - name: train num_bytes: 1101443348.656 num_examples: 7748 - name: test num_bytes: 89786903.0 num_examples: 567 download_size: 3546373791 dataset_size: 1191230251.656 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
QuanHoangNgoc/EVJ_Cluster	QuanHoangNgoc	"2024-10-22T13:55:58Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-10-22T13:55:09Z"	--- dataset_info: features: - name: answer dtype: string - name: cluster dtype: int32 - name: image dtype: image - name: prompt dtype: string splits: - name: train num_bytes: 965568274.42 num_examples: 5820 - name: test num_bytes: 358795481.815 num_examples: 2495 download_size: 1239772291 dataset_size: 1324363756.235 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
QuanHoangNgoc/EVJ_Cluster-Normal	QuanHoangNgoc	"2024-10-23T09:19:34Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-10-23T09:18:39Z"	--- dataset_info: features: - name: answer dtype: string - name: cluster dtype: int32 - name: image dtype: image - name: prompt dtype: string splits: - name: li_train num_bytes: 900073595.5 num_examples: 5820 - name: li_test num_bytes: 354791631.125 num_examples: 2495 download_size: 1239073417 dataset_size: 1254865226.625 configs: - config_name: default data_files: - split: li_train path: data/li_train-* - split: li_test path: data/li_test-* ---
ayyuce/drugs	ayyuce	"2024-11-06T23:31:49Z"	0	[ "license:mit", "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-11-06T23:30:48Z"	--- license: mit ---
QuanHoangNgoc/EVJ_Cluster-Expanded	QuanHoangNgoc	"2024-11-13T14:19:21Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-11-13T14:16:49Z"	--- dataset_info: features: - name: answer dtype: string - name: cluster dtype: int32 - name: image dtype: image - name: prompt dtype: string - name: description dtype: string splits: - name: li_train num_bytes: 901224571.5 num_examples: 5820 - name: li_test num_bytes: 355286984.125 num_examples: 2495 download_size: 1239503465 dataset_size: 1256511555.625 configs: - config_name: default data_files: - split: li_train path: data/li_train-* - split: li_test path: data/li_test-* ---
shroom-semeval25/hallucinated_answer_generated_dataset_cleaned	shroom-semeval25	"2024-11-13T22:39:51Z"	0	[ "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-11-13T22:34:17Z"	--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int32 - name: text sequence: string - name: correct_answer_generated dtype: string - name: hallucinated_answer_generated dtype: string splits: - name: train num_bytes: 397086774 num_examples: 373848 - name: validation num_bytes: 49601442 num_examples: 46731 - name: test num_bytes: 49545525 num_examples: 46732 download_size: 319248685 dataset_size: 496233741 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
QuanHoangNgoc/MS_TestSet_5k	QuanHoangNgoc	"2024-12-27T06:56:58Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2024-12-27T06:55:30Z"	--- dataset_info: features: - name: image dtype: image - name: caption sequence: string splits: - name: test num_bytes: 2417550920.0 num_examples: 5000 download_size: 2417029684 dataset_size: 2417550920.0 configs: - config_name: default data_files: - split: test path: data/test-* ---
kevin017/tokenized_bioS_QA_b_city_large	kevin017	"2025-02-28T07:22:57Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-01-09T20:17:56Z"	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87638953 num_examples: 34061 - name: test num_bytes: 87641526 num_examples: 34062 download_size: 12501009 dataset_size: 175280479 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
kevin017/tokenized_bioS_QA_b_date_large	kevin017	"2025-02-28T07:23:07Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-01-09T20:18:05Z"	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87690413 num_examples: 34081 - name: test num_bytes: 87664683 num_examples: 34071 download_size: 13740130 dataset_size: 175355096 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
kevin017/tokenized_bioS_QA_c_city_large	kevin017	"2025-02-28T07:23:17Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-01-09T20:18:15Z"	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87170667 num_examples: 33879 - name: test num_bytes: 87165521 num_examples: 33877 download_size: 10015228 dataset_size: 174336188 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
kevin017/tokenized_bioS_QA_c_name_large	kevin017	"2025-02-28T07:23:28Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-01-09T20:18:22Z"	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87232419 num_examples: 33903 - name: test num_bytes: 87214408 num_examples: 33896 download_size: 12468376 dataset_size: 174446827 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
kevin017/tokenized_bioS_QA_univ_large	kevin017	"2025-02-28T07:23:49Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-01-09T20:18:39Z"	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87353350 num_examples: 33950 - name: test num_bytes: 87343058 num_examples: 33946 download_size: 13016656 dataset_size: 174696408 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
QuanHoangNgoc/MS-Flickr30k	QuanHoangNgoc	"2025-01-19T03:36:29Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-01-19T03:31:54Z"	--- dataset_info: features: - name: image dtype: image - name: caption dtype: string splits: - name: test num_bytes: 6740690168.25 num_examples: 36014 download_size: 6721561298 dataset_size: 6740690168.25 configs: - config_name: default data_files: - split: test path: data/test-* ---
roomtour3d/Self-Critic-Hallucination_withGT	roomtour3d	"2025-02-25T07:09:15Z"	0	[ "license:mit", "size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-02-25T06:51:38Z"	--- license: mit dataset_info: features: - name: ds_name dtype: string - name: image dtype: image - name: question dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: origin_dataset dtype: string - name: origin_split dtype: string - name: idx dtype: string - name: image_path dtype: string - name: gt list: - name: answer dtype: string - name: answer_id dtype: int64 splits: - name: train num_bytes: 4414647639.4 num_examples: 28696 download_size: 4391984529 dataset_size: 4414647639.4 configs: - config_name: default data_files: - split: train path: data/train-* ---
inkoziev/ArsPoetica	inkoziev	"2025-03-01T04:38:37Z"	1	[ "task_categories:text-generation", "language:ru", "license:cc-by-4.0", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "poetry" ]	[ "text-generation" ]	"2025-02-27T16:28:19Z"	--- license: cc-by-4.0 task_categories: - text-generation language: - ru tags: - poetry pretty_name: Ars Poetica size_categories: - 1K<n<10K --- # Ars Poetica The Ars Poetica dataset is a collection of Russian-language poetry from the 19th and 20th centuries, annotated with stress marks. This dataset is designed to support research in generative poetry, computational linguistics, and related fields. Stress marks were automatically assigned using the [RussianPoetryScansionTool](https://github.com/Koziev/RussianPoetryScansionTool) library. While the dataset has undergone selective manual validation, users should be aware of potential inaccuracies due to the automated process. ## Example ``` За́йку бро́сила хозя́йка — Под дождё́м оста́лся за́йка. Со скаме́йки сле́зть не мо́г, Ве́сь до ни́точки промо́к. ``` ## Citing If you use this dataset in your research or projects, please cite it as follows: ```bibtex @misc{Conversations, author = {Ilya Koziev}, title = {Ars Poetica Dataset}, year = {2025}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/datasets/inkoziev/ArsPoetica}}, } ``` ## License This dataset is licensed under the [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/) license, which permits non-commercial use only. For commercial use, please contact the author at [inkoziev@gmail.com]. By using this dataset, you agree to: - Provide proper attribution to the author. - Refrain from using the dataset for commercial purposes without explicit permission. ## Other resources If you are interested in stress placement and homograph resolution, check out our [Homograph Resolution Evaluation Dataset](https://huggingface.co/datasets/inkoziev/HomographResolutionEval) and [Rifma](https://github.com/Koziev/Rifma) datasets. ## Limitations - Automated Processing: The dataset was generated through automated methods with only selective manual validation. As a result, some poems may contain misspellings, typos, or other imperfections. - Limited Scope: The dataset does not encompass the full range of Russian poetic works. Many genres, forms, and longer compositions are excluded, making it unsuitable as a comprehensive anthology of Russian poetry.
caitwong/balanced_translation_dataset4	caitwong	"2025-03-01T17:49:51Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-02-28T10:42:27Z"	--- dataset_info: - config_name: batch_1 features: - name: None dtype: string - name: en dtype: string - name: vi dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 - name: th dtype: string - name: conversation_id dtype: string - name: category dtype: string - name: zh dtype: string - name: hi dtype: string - name: ms dtype: string splits: - name: train num_bytes: 2470346 num_examples: 5654 download_size: 1201569 dataset_size: 2470346 - config_name: batch_2 features: - name: en dtype: string - name: tl dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 - name: conversation_id dtype: string - name: category dtype: string - name: zh dtype: string - name: id dtype: string splits: - name: train num_bytes: 2192989 num_examples: 3222 download_size: 1213459 dataset_size: 2192989 - config_name: batch_3 features: - name: en dtype: string - name: id dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 splits: - name: train num_bytes: 1254295 num_examples: 5072 download_size: 803079 dataset_size: 1254295 - config_name: batch_4 features: - name: None dtype: string - name: en dtype: string - name: vi dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 - name: conversation_id dtype: string - name: category dtype: string - name: zh dtype: string - name: th dtype: string splits: - name: train num_bytes: 6529648 num_examples: 8992 download_size: 3312547 dataset_size: 6529648 - config_name: batch_5 features: - name: tl dtype: string - name: en dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 splits: - name: train num_bytes: 2627409 num_examples: 3137 download_size: 1475207 dataset_size: 2627409 configs: - config_name: batch_1 data_files: - split: train path: batch_1/train-* - config_name: batch_2 data_files: - split: train path: batch_2/train-* - config_name: batch_3 data_files: - split: train path: batch_3/train-* - config_name: batch_4 data_files: - split: train path: batch_4/train-* - config_name: batch_5 data_files: - split: train path: batch_5/train-* ---
simwit/medmoe-vqa-rad	simwit	"2025-03-01T07:52:46Z"	0	[ "license:apache-2.0", "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-02-28T10:50:55Z"	--- license: apache-2.0 dataset_info: features: - name: image dtype: image - name: question dtype: string - name: answer dtype: string - name: modality dtype: string - name: answer_type dtype: string splits: - name: test_all num_bytes: 23826356.0 num_examples: 451 - name: test_open num_bytes: 9281911.0 num_examples: 179 - name: test_closed num_bytes: 14544445.0 num_examples: 272 download_size: 26472530 dataset_size: 47652712.0 configs: - config_name: default data_files: - split: test_all path: data/test_all-* - split: test_open path: data/test_open-* - split: test_closed path: data/test_closed-* ---
g-ronimo/IN1k256-AR-buckets-latents_dc-ae-f32c32-sana-1.0_	g-ronimo	"2025-02-28T19:54:06Z"	0	[ "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-02-28T17:52:21Z"	--- dataset_info: features: - name: label dtype: string - name: latent sequence: sequence: sequence: sequence: float32 splits: - name: train_AR_4_to_3.part_0 num_bytes: 1144094328 num_examples: 100000 - name: train_AR_4_to_3.part_1 num_bytes: 1144088430 num_examples: 100000 - name: train_AR_3_to_4.part_0 num_bytes: 1169764996 num_examples: 100000 - name: train_AR_4_to_3.part_2 num_bytes: 1144091474 num_examples: 100000 download_size: 1573133511 dataset_size: 4602039228 configs: - config_name: default data_files: - split: train_AR_4_to_3.part_0 path: data/train_AR_4_to_3.part_0-* - split: train_AR_4_to_3.part_1 path: data/train_AR_4_to_3.part_1-* - split: train_AR_3_to_4.part_0 path: data/train_AR_3_to_4.part_0-* - split: train_AR_4_to_3.part_2 path: data/train_AR_4_to_3.part_2-* ---
yvngexe/data_generated_by_armo	yvngexe	"2025-03-01T14:18:28Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-02-28T23:26:25Z"	--- dataset_info: features: - name: prompt_id dtype: string - name: prompt dtype: string - name: response_0 dtype: string - name: response_1 dtype: string - name: response_2 dtype: string - name: response_3 dtype: string - name: response_4 dtype: string - name: response_0_reward dtype: float64 - name: response_1_reward dtype: float64 - name: response_2_reward dtype: float64 - name: response_3_reward dtype: float64 - name: response_4_reward dtype: float64 splits: - name: train num_bytes: 591568112 num_examples: 61814 download_size: 319605004 dataset_size: 591568112 configs: - config_name: default data_files: - split: train path: data/train-* ---
ZStack-AI/LongDPO_openqa	ZStack-AI	"2025-03-01T04:45:14Z"	0	[ "license:apache-2.0", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "region:us" ]	null	"2025-03-01T03:41:58Z"	--- license: apache-2.0 ---
inkoziev/HomographResolutionEval	inkoziev	"2025-03-01T04:32:49Z"	1	[ "task_categories:text2text-generation", "language:ru", "license:cc-by-4.0", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "homograph_resolution", "accentuation" ]	[ "text2text-generation" ]	"2025-03-01T04:14:23Z"	--- license: cc-by-4.0 task_categories: - text2text-generation language: - ru tags: - homograph_resolution - accentuation pretty_name: Homograph Resulution Evaluation Dataset size_categories: - 1K<n<10K --- # Homograph Resolution Evaluation Dataset This dataset is designed to evaluate the performance of Text-to-Speech (TTS) systems and Language Models (LLMs) in resolving homographs in the Russian language. It contains carefully curated sentences, each featuring at least one homograph with the correct stress indicated. The dataset is particularly useful for assessing stress assignment tasks in TTS systems and LLMs. ## Key Features - Language: Russian - Focus: Homograph resolution and stress assignment - Unique Samples: All sentences are original and highly unlikely to be present in existing training datasets. - Stress Annotation: Correct stress marks are provided for homographs, enabling precise evaluation. ## Dataset Fields - `context`: A sentence containing one or more homographs. - `homograph`: The homograph with the correct stress mark. - `accentuated_context`: The full sentence with correct stress marks applied. Note: When evaluating, stress marks on words other than the homograph can be ignored. ## Limitations 1. Single Stress Variant: Each sample provides only one stress variant for a homograph, even if the homograph appears multiple times in the sentence (though such cases are rare). 2. Limited Homograph Coverage: The dataset includes a small subset of homographs in the Russian language and is not exhaustive. ## Intended Use This dataset is ideal for: - Evaluating TTS systems on homograph resolution and stress assignment. - Benchmarking LLMs on their ability to handle ambiguous linguistic constructs. - Research in computational linguistics, particularly in stress disambiguation and homograph resolution. ## Citing the Dataset If you use this dataset in your research or projects, please cite it as follows: ```bibtex @misc{HomographResolutionEval, author = {Ilya Koziev}, title = {Homograph Resolution Evaluation Dataset}, year = {2025}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/datasets/inkoziev/HomographResolutionEval}} }
RyanYr/simpleRLZero_matheval	RyanYr	"2025-03-01T04:21:24Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T04:21:23Z"	--- dataset_info: features: - name: data_source dtype: string - name: problem dtype: string - name: solution dtype: string - name: answer dtype: string - name: prompt list: - name: content dtype: string - name: role dtype: string - name: reward_model struct: - name: ground_truth dtype: string - name: style dtype: string - name: responses dtype: string - name: gt_ans dtype: string - name: extracted_solution dtype: string - name: rm_scores dtype: bool splits: - name: train num_bytes: 6208004 num_examples: 1517 download_size: 2469747 dataset_size: 6208004 configs: - config_name: default data_files: - split: train path: data/train-* ---
introvoyz041/Lilac	introvoyz041	"2025-03-01T04:34:24Z"	0	[ "license:apache-2.0", "region:us" ]	null	"2025-03-01T04:34:00Z"	--- license: apache-2.0 ---
RyanYr/RLHFlowOnlineDPOPPOZero_matheval	RyanYr	"2025-03-01T04:34:28Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T04:34:26Z"	--- dataset_info: features: - name: data_source dtype: string - name: problem dtype: string - name: solution dtype: string - name: answer dtype: string - name: prompt list: - name: content dtype: string - name: role dtype: string - name: reward_model struct: - name: ground_truth dtype: string - name: style dtype: string - name: responses dtype: string - name: gt_ans dtype: string - name: extracted_solution dtype: string - name: rm_scores dtype: bool splits: - name: train num_bytes: 5914469 num_examples: 1517 download_size: 2481535 dataset_size: 5914469 configs: - config_name: default data_files: - split: train path: data/train-* ---
introvoyz041/Llm4sd	introvoyz041	"2025-03-01T04:41:48Z"	0	[ "license:apache-2.0", "size_categories:10K<n<100K", "format:text", "modality:text", "library:datasets", "library:mlcroissant", "region:us" ]	null	"2025-03-01T04:41:28Z"	--- license: apache-2.0 ---
RyanYr/Qwen2.5-7B-DPO-Zero_matheval	RyanYr	"2025-03-01T04:47:45Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T04:47:44Z"	--- dataset_info: features: - name: data_source dtype: string - name: problem dtype: string - name: solution dtype: string - name: answer dtype: string - name: prompt list: - name: content dtype: string - name: role dtype: string - name: reward_model struct: - name: ground_truth dtype: string - name: style dtype: string - name: responses dtype: string - name: gt_ans dtype: string - name: extracted_solution dtype: string - name: rm_scores dtype: bool splits: - name: train num_bytes: 7259615 num_examples: 1517 download_size: 2543503 dataset_size: 7259615 configs: - config_name: default data_files: - split: train path: data/train-* ---
meowterspace42/gretel-dd-glue-wnli	meowterspace42	"2025-03-01T07:18:31Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T04:53:41Z"	--- dataset_info: features: - name: seed_examples dtype: string - name: writing_style dtype: string - name: domain dtype: string - name: target_label dtype: string - name: glue_example dtype: string - name: eval_metrics dtype: string splits: - name: train num_bytes: 1743260 num_examples: 1798 download_size: 203981 dataset_size: 1743260 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/test_1	Isylimanov099	"2025-03-01T05:00:44Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:00:42Z"	--- dataset_info: features: - name: Description dtype: string - name: Client dtype: string - name: Lawyer dtype: string splits: - name: train num_bytes: 88010 num_examples: 100 download_size: 36369 dataset_size: 88010 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/FAInAselmOon	Isylimanov099	"2025-03-01T05:01:37Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:01:35Z"	--- dataset_info: features: - name: Описание dtype: float64 - name: Вопрос dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 3062 num_examples: 13 download_size: 4077 dataset_size: 3062 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/Test-books	Isylimanov099	"2025-03-01T05:05:14Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:05:10Z"	--- dataset_info: features: - name: Описание dtype: string - name: Вопрос dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 7866 num_examples: 29 download_size: 7873 dataset_size: 7866 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/kamila09	Isylimanov099	"2025-03-01T05:05:18Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:05:16Z"	--- dataset_info: features: - name: Описание dtype: string - name: Вопросы dtype: string - name: Ответы dtype: string splits: - name: train num_bytes: 8603 num_examples: 50 download_size: 6236 dataset_size: 8603 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/Koala	Isylimanov099	"2025-03-01T05:05:25Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:05:23Z"	--- dataset_info: features: - name: Описание dtype: string - name: Вопрос dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 16480 num_examples: 43 download_size: 10197 dataset_size: 16480 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/Travel	Isylimanov099	"2025-03-01T05:06:35Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:06:32Z"	--- dataset_info: features: - name: 'Unnamed: 0' dtype: float64 - name: 描述 dtype: string - name: 问题 dtype: string - name: 回答 dtype: string splits: - name: train num_bytes: 9557 num_examples: 16 download_size: 9231 dataset_size: 9557 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/IT-Venera	Isylimanov099	"2025-03-01T05:08:30Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:08:25Z"	--- dataset_info: features: - name: 'Unnamed: 0' dtype: string - name: 'Unnamed: 1' dtype: string - name: 'Unnamed: 2' dtype: string - name: 'Unnamed: 3' dtype: string splits: - name: train num_bytes: 66500 num_examples: 75 download_size: 28823 dataset_size: 66500 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/a.bolotbekovvvna	Isylimanov099	"2025-03-01T05:08:35Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:08:33Z"	--- dataset_info: features: - name: ОПИСАНИЕ dtype: string - name: ВОПРОС dtype: string - name: ОТВЕТ dtype: string splits: - name: train num_bytes: 7046 num_examples: 20 download_size: 6608 dataset_size: 7046 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/asel	Isylimanov099	"2025-03-01T05:12:05Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:12:02Z"	--- dataset_info: features: - name: Описание dtype: string - name: Вопросы dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 1516 num_examples: 4 download_size: 3866 dataset_size: 1516 configs: - config_name: default data_files: - split: train path: data/train-* ---
Isylimanov099/JanybekovaAijamal	Isylimanov099	"2025-03-01T05:20:32Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T05:20:30Z"	--- dataset_info: features: - name: Описание dtype: string - name: Вопрос dtype: string - name: Ответ dtype: float64 - name: 'Unnamed: 3' dtype: float64 - name: Кв. 3 dtype: float64 - name: Кв. 4 dtype: float64 splits: - name: train num_bytes: 20168 num_examples: 277 download_size: 6889 dataset_size: 20168 configs: - config_name: default data_files: - split: train path: data/train-* ---
jmhb/VidDiffBench	jmhb	"2025-03-01T08:23:54Z"	1	[ "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "modality:video", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "video" ]	null	"2025-03-01T06:08:38Z"	--- tags: - video dataset_info: features: - name: sample_key dtype: string - name: vid0_thumbnail dtype: image - name: vid1_thumbnail dtype: image - name: videos dtype: string - name: action dtype: string - name: action_name dtype: string - name: action_description dtype: string - name: source_dataset dtype: string - name: sample_hash dtype: int64 - name: retrieval_frames dtype: string - name: differences_annotated dtype: string - name: differences_gt dtype: string - name: domain dtype: string - name: split dtype: string - name: n_differences_open_prediction dtype: int64 splits: - name: test num_bytes: 15219230.154398564 num_examples: 549 download_size: 6445835 dataset_size: 15219230.154398564 configs: - config_name: default data_files: - split: test path: data/test-* --- # Dataset card for "VidDiffBench" This is the dataset / benchmark for [Video Action Differencing](https://openreview.net/forum?id=3bcN6xlO6f) (ICLR 2025), a new task that compares how an action is performed between two videos. This page introduces the task, the dataset structure, and how to access the data. See the paper for details on dataset construction. The code for running evaluation, and for benchmarking popular LMMs is at [https://jmhb0.github.io/viddiff](https://jmhb0.github.io/viddiff). ``` @inproceedings{burgessvideo, title={Video Action Differencing}, author={Burgess, James and Wang, Xiaohan and Zhang, Yuhui and Rau, Anita and Lozano, Alejandro and Dunlap, Lisa and Darrell, Trevor and Yeung-Levy, Serena}, booktitle={The Thirteenth International Conference on Learning Representations} } ``` # The Video Action Differencing task: closed and open evaluation The Video Action Differencing task compares two videos of the same action. The goal is to identify differences in how the action is performed, where the differences are expressed in natural language. ![morecontent](https://raw.githubusercontent.com/jmhb0/jmhb0.github.io/main/images/pull%20fig-5.jpg) In closed evaluation: - Input: two videos of the same action, action description string, a list of candidate difference strings. - Output: for each difference string, either 'a' if the statement applies more to video a, or 'b' if it applies more to video 'b'. In open evaluation, the model must generate the difference strings: - Input: two videos of the same action, action description string, a number 'n_differences'. - Output: a list of difference strings (at most 'n_differences'). For each difference string, 'a' if the statement applies more to video a, or 'b' if it applies more to video 'b'. <!-- Some more details on these evaluation modes. See the paper for more discussion: - In closed eval, we only provide difference strings where the gt label is 'a' or 'b'; if the gt label is 'c' meaning "not different", it's skipped. This is because different annotators (or models) may have different calibration: a different judgement of "how different is different enough". - In open evaluation, the model is allowed to predict at most `n_differences`, which we set to be 1.5x the number of differences we included in our annotation taxonomy. This is because there may be valid differences not in our annotation set, and models should not be penalized for that. But a limit is required to prevent cheating by enumerating too many possible differences. The eval scripts are at [https://jmhb0.github.io/viddiff](https://jmhb0.github.io/viddiff). --> # Dataset structure After following the 'getting the data' section: we have `dataset` as a HuggingFace dataset and `videos` as a list. For row `i`: video A is `videos[0][i]`, video B is `videos[1][i]`, and `dataset[i]` is the annotation for the difference between the videos. The videos: - `videos[0][i]['video']` and is a numpy array with shape `(nframes,H,W,3)`. - `videos[0][i]['fps_original']` is an int, frames per second. The annotations in `dataset`: - `sample_key` a unique key. - `videos` metadata about the videos A and B used by the dataloader: the video filename, and the start and end frames. - `action` action key like "fitness_2" - `action_name` a short action name, like "deadlift" - `action_description` a longer action description, like "a single free weight deadlift without any weight" - `source_dataset` the source dataset for the videos (but not annotation), e.g. 'humman' [here](https://caizhongang.com/projects/HuMMan/). - `split` difficulty split, one of `{'easy', 'medium', 'hard'}` - `n_differences_open_prediction` in open evaluation, the max number of difference strings the model is allowed to generate. - `differences_annotated` a dict with the difference strings, e.g: ``` { "0": { "description": "the feet stance is wider", "name": "feet stance wider", "num_frames": "1", }, "1": { "description": "the speed of hip rotation is faster", "name": "speed", "num_frames": "gt_1", }, "2" : null, ... ``` - and these keys are: - the key is the 'key_difference' - `description` is the 'difference string' (passed as input in closed eval, or the model must generate a semantically similar string in open eval). - `num_frames` (not used) is '1' if an LMM could solve it from a single (well-chosen) frame, or 'gt_1' if more frames are needed. - Some values might be `null`. This is because the Huggingface datasets enforces that all elements in a column have the same schema. - `differences_gt` has the gt label, e.g. `{"0": "b", "1":"a", "2":null}`. For example, difference "the feet stance is wider" applies more to video B. - `domain` activity domain. One of `{'fitness', 'ballsports', 'diving', 'surgery', 'music'}`. # Getting the data Getting the dataset requires a few steps. We distribute the annotations, but since we don't own the videos, you'll have to download them elsewhere. Get the annotations First, get the annotations from the hub like this: ``` from datasets import load_dataset repo_name = "jmhb/VidDiffBench" dataset = load_dataset(repo_name) ``` Get the videos We get videos from prior works (which should be cited if you use the benchmark - see the end of this doc). The source dataset is in the dataset column `source_dataset`. First, download some `.py` files from this repo into your local `data/` file. ``` GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/jmhb/VidDiffBench data/ ``` A few datasets let us redistribute videos, so you can download them from this HF repo like this: ``` python data/download_data.py ``` If you ONLY need the 'easy' split, you can stop here. The videos includes the source datasets [Humann](https://caizhongang.com/projects/HuMMan/) (and 'easy' only draws from this data) and [JIGSAWS](https://cirl.lcsr.jhu.edu/research/hmm/datasets/jigsaws_release/). For 'medium' and 'hard' splits, you'll need to download these other datasets from the EgoExo4D and FineDiving. Here's how to do that: Download EgoExo4d videos These are needed for 'medium' and 'hard' splits. First Request an access key from the [docs](https://docs.ego-exo4d-data.org/getting-started/) (it takes 48hrs). Then follow the instructions to install the CLI download tool `egoexo`. We only need a small number of these videos, so get the uids list from `data/egoexo4d_uids.json` and use `egoexo` to download: ``` uids=$(jq -r '.[]' data/egoexo4d_uids.json \| tr '\n' ' ' \| sed 's/ $//') egoexo -o data/src_EgoExo4D --parts downscaled_takes/448 --uids $uids ``` Common issue: remember to put your access key into `~/.aws/credentials`. Download FineDiving videos These are needed for 'medium' split. Follow the instructions in [the repo](https://github.com/xujinglin/FineDiving) to request access (it takes at least a day), download the whole thing, and set up a link to it: ``` ln -s <path_to_fitnediving> data/src_FineDiving ``` Making the final dataset with videos Install these packages: ``` pip install numpy Pillow datasets decord lmdb tqdm huggingface_hub ``` Now run: ``` from data.load_dataset import load_dataset, load_all_videos dataset = load_dataset(splits=['easy'], subset_mode="0") # splits are one of {'easy','medium','hard'} videos = load_all_videos(dataset, cache=True, cache_dir="cache/cache_data") ``` For row `i`: video A is `videos[0][i]`, video B is `videos[1][i]`, and `dataset[i]` is the annotation for the difference between the videos. For video A, the video itself is `videos[0][i]['video']` and is a numpy array with shape `(nframes,3,H,W)`; the fps is in `videos[0][i]['fps_original']`. By passing the argument `cache=True` to `load_all_videos`, we create a cache directory at `cache/cache_data/`, and save copies of the videos using numpy memmap (total directory size for the whole dataset is 55Gb). Loading the videos and caching will take a few minutes per split (faster for the 'easy' split), and about 25mins for the whole dataset. But on subsequent runs, it should be fast - a few seconds for the whole dataset. Finally, you can get just subsets, for example setting `subset_mode='3_per_action'` will take 3 video pairs per action, while `subset_mode="0"` gets them all. # More dataset info We have more dataset metadata in this dataset repo: - Differences taxonomy `data/difference_taxonomy.csv`. - Actions and descriptions `data/actions.csv`. # License The annotations and all other non-video metadata is realeased under an MIT license. The videos retain the license of the original dataset creators, and the source dataset is given in dataset column `source_dataset`. - EgoExo4D, license is online at [this link](https://ego4d-data.org/pdfs/Ego-Exo4D-Model-License.pdf) - JIGSAWS release notes at [this link](https://cirl.lcsr.jhu.edu/research/hmm/datasets/jigsaws_release/ ) - Humman uses "S-Lab License 1.0" at [this link](https://caizhongang.com/projects/HuMMan/license.txt) - FineDiving use [this MIT license](https://github.com/xujinglin/FineDiving/blob/main/LICENSE) # Citation Below is the citation for our paper, and the original source datasets: ``` @inproceedings{burgessvideo, title={Video Action Differencing}, author={Burgess, James and Wang, Xiaohan and Zhang, Yuhui and Rau, Anita and Lozano, Alejandro and Dunlap, Lisa and Darrell, Trevor and Yeung-Levy, Serena}, booktitle={The Thirteenth International Conference on Learning Representations} } @inproceedings{cai2022humman, title={{HuMMan}: Multi-modal 4d human dataset for versatile sensing and modeling}, author={Cai, Zhongang and Ren, Daxuan and Zeng, Ailing and Lin, Zhengyu and Yu, Tao and Wang, Wenjia and Fan, Xiangyu and Gao, Yang and Yu, Yifan and Pan, Liang and Hong, Fangzhou and Zhang, Mingyuan and Loy, Chen Change and Yang, Lei and Liu, Ziwei}, booktitle={17th European Conference on Computer Vision, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part VII}, pages={557--577}, year={2022}, organization={Springer} } @inproceedings{parmar2022domain, title={Domain Knowledge-Informed Self-supervised Representations for Workout Form Assessment}, author={Parmar, Paritosh and Gharat, Amol and Rhodin, Helge}, booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XXXVIII}, pages={105--123}, year={2022}, organization={Springer} } @inproceedings{grauman2024ego, title={Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives}, author={Grauman, Kristen and Westbury, Andrew and Torresani, Lorenzo and Kitani, Kris and Malik, Jitendra and Afouras, Triantafyllos and Ashutosh, Kumar and Baiyya, Vijay and Bansal, Siddhant and Boote, Bikram and others}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={19383--19400}, year={2024} } @inproceedings{gao2014jhu, title={Jhu-isi gesture and skill assessment working set (jigsaws): A surgical activity dataset for human motion modeling}, author={Gao, Yixin and Vedula, S Swaroop and Reiley, Carol E and Ahmidi, Narges and Varadarajan, Balakrishnan and Lin, Henry C and Tao, Lingling and Zappella, Luca and B{\'e}jar, Benjam{\i}n and Yuh, David D and others}, booktitle={MICCAI workshop: M2cai}, volume={3}, number={2014}, pages={3}, year={2014} } ```
mshojaei77/PDC	mshojaei77	"2025-03-01T06:30:06Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:10:23Z"	--- dataset_info: features: - name: text dtype: string - name: file_name dtype: string splits: - name: train num_bytes: 1624495382 num_examples: 13111 download_size: 549673162 dataset_size: 1624495382 configs: - config_name: default data_files: - split: train path: data/train-* ---
simwit/medmoe-slake	simwit	"2025-03-01T07:53:30Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:27:40Z"	--- dataset_info: features: - name: image dtype: image - name: question dtype: string - name: answer dtype: string - name: modality dtype: string - name: answer_type dtype: string splits: - name: test_all num_bytes: 109097147.213 num_examples: 1061 - name: test_open num_bytes: 69131481.0 num_examples: 645 - name: test_closed num_bytes: 37653859.0 num_examples: 416 download_size: 27747526 dataset_size: 215882487.213 configs: - config_name: default data_files: - split: test_all path: data/test_all-* - split: test_open path: data/test_open-* - split: test_closed path: data/test_closed-* ---
Hkang/summarize_sft-test_lm-EleutherAI_pythia-1b_seed-42_numex-250_20K-BON_alpha-0.7_temp-0.7_64	Hkang	"2025-03-01T06:29:50Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:29:49Z"	--- dataset_info: features: - name: id dtype: string - name: subreddit dtype: string - name: title dtype: string - name: post dtype: string - name: summary dtype: string - name: query_input_ids sequence: int64 - name: query_attention_mask sequence: int64 - name: query dtype: string - name: reference_response dtype: string - name: reference_response_input_ids sequence: int64 - name: reference_response_attention_mask sequence: int64 - name: reference_response_token_len dtype: int64 - name: query_reference_response dtype: string - name: query_reference_response_input_ids sequence: int64 - name: query_reference_response_attention_mask sequence: int64 - name: query_reference_response_token_response_label sequence: int64 - name: query_reference_response_token_len dtype: int64 - name: model_response dtype: string splits: - name: test num_bytes: 6845542 num_examples: 250 download_size: 1156613 dataset_size: 6845542 configs: - config_name: default data_files: - split: test path: data/test-* ---
LunaCookie/RPG-datasets	LunaCookie	"2025-03-01T06:32:38Z"	0	[ "license:openrail", "size_categories:n<1K", "format:audiofolder", "modality:audio", "library:datasets", "library:mlcroissant", "region:us" ]	null	"2025-03-01T06:31:09Z"	--- license: openrail ---
simwit/medmoe-path-vqa	simwit	"2025-03-01T07:50:59Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:31:44Z"	--- dataset_info: features: - name: image dtype: image - name: question dtype: string - name: answer dtype: string - name: answer_type dtype: string splits: - name: test_all num_bytes: 487625910.222 num_examples: 6761 - name: test_open num_bytes: 428189626.97 num_examples: 3370 - name: test_closed num_bytes: 417624057.619 num_examples: 3391 download_size: 475692126 dataset_size: 1333439594.811 configs: - config_name: default data_files: - split: test_all path: data/test_all-* - split: test_open path: data/test_open-* - split: test_closed path: data/test_closed-* ---
isaiahbjork/showui-reasoning	isaiahbjork	"2025-03-01T06:32:30Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:32:01Z"	--- dataset_info: features: - name: conversation list: - name: content list: - name: text dtype: string - name: type dtype: string - name: role dtype: string - name: image dtype: binary splits: - name: train num_bytes: 9372012432 num_examples: 20000 download_size: 714885901 dataset_size: 9372012432 configs: - config_name: default data_files: - split: train path: data/train-* ---
Dhruveshsd/dvs	Dhruveshsd	"2025-03-01T06:33:45Z"	0	[ "license:bigscience-openrail-m", "region:us" ]	null	"2025-03-01T06:33:45Z"	--- license: bigscience-openrail-m ---
Yiheyihe/galaxea-r1-shelf-1ep-normalized	Yiheyihe	"2025-03-01T09:04:58Z"	0	[ "task_categories:robotics", "license:apache-2.0", "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "LeRobot" ]	[ "robotics" ]	"2025-03-01T06:42:10Z"	--- license: apache-2.0 task_categories: - robotics tags: - LeRobot configs: - config_name: default data_files: data//.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - Homepage: [More Information Needed] - Paper: [More Information Needed] - License: apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": null, "total_episodes": 1, "total_frames": 508, "total_tasks": 1, "total_videos": 3, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "observation.state": { "dtype": "float32", "shape": [ 21 ] }, "action": { "dtype": "float32", "shape": [ 21 ] }, "observation.images.head": { "dtype": "video", "shape": [ 3, 94, 168 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 94, "video.width": 168, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.left_wrist": { "dtype": "video", "shape": [ 3, 94, 168 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 94, "video.width": 168, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.right_wrist": { "dtype": "video", "shape": [ 3, 94, 168 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 94, "video.width": 168, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation BibTeX: ```bibtex [More Information Needed] ```
gajanhcc/fashion-detail-query-10images	gajanhcc	"2025-03-01T06:50:24Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:50:22Z"	--- dataset_info: features: - name: image dtype: image - name: item_ID dtype: string - name: query dtype: string - name: title dtype: string - name: position dtype: int64 - name: specific_detail_query dtype: string splits: - name: train num_bytes: 96642.7 num_examples: 7 - name: test num_bytes: 41418.3 num_examples: 3 download_size: 144469 dataset_size: 138061.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
jinchenliuljc/FinSumCOT	jinchenliuljc	"2025-03-01T06:58:05Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:51:50Z"	--- dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: text dtype: string - name: summary dtype: string - name: deepseek_summary dtype: string - name: deepseek_reasoning dtype: string splits: - name: train num_bytes: 86154 num_examples: 5 download_size: 66081 dataset_size: 86154 configs: - config_name: default data_files: - split: train path: data/train-* ---
gajanhcc/fashion-detail-query-annotated-10images	gajanhcc	"2025-03-01T07:06:29Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:52:49Z"	--- dataset_info: features: - name: image dtype: image - name: item_ID dtype: string - name: query dtype: string - name: title dtype: string - name: position dtype: int64 - name: original_image dtype: image - name: specific_detail_query dtype: string splits: - name: train num_bytes: 117483829.6 num_examples: 800 - name: test num_bytes: 29370957.4 num_examples: 200 download_size: 146828393 dataset_size: 146854787.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
svjack/Genshin_Impact_Yae_Miko_MMD_Video_Dataset	svjack	"2025-03-01T11:55:36Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:video", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T06:58:10Z"	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: video dtype: video splits: - name: train num_bytes: 1447150184.556 num_examples: 1061 download_size: 159078 dataset_size: 1447150184.556 --- <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/8aCjIslNTHwNqEENpgpg6.mp4"></video> Reorganized version of [`Wild-Heart/Disney-VideoGeneration-Dataset`](https://huggingface.co/datasets/Wild-Heart/Disney-VideoGeneration-Dataset). This is needed for [Mochi-1 fine-tuning](https://github.com/genmoai/mochi/tree/aba74c1b5e0755b1fa3343d9e4bd22e89de77ab1/demos/fine_tuner).
gymprathap/Driver-Distracted-Dataset	gymprathap	"2025-03-01T08:29:19Z"	0	[ "language:en", "license:cc", "size_categories:100K<n<1M", "modality:image", "region:us", "art" ]	null	"2025-03-01T07:04:54Z"	--- license: cc language: - en tags: - art size_categories: - 100K<n<1M ---
gajanhcc/fashion-detail-query-annotated-1000images	gajanhcc	"2025-03-01T07:09:51Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:09:43Z"	--- dataset_info: features: - name: image dtype: image - name: item_ID dtype: string - name: query dtype: string - name: title dtype: string - name: position dtype: int64 - name: original_image dtype: image - name: specific_detail_query dtype: string splits: - name: train num_bytes: 117483829.6 num_examples: 800 - name: test num_bytes: 29370957.4 num_examples: 200 download_size: 146828393 dataset_size: 146854787.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
khcho1954/ragas-test-dataset	khcho1954	"2025-03-01T07:11:43Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:09:50Z"	--- dataset_info: features: - name: contexts dtype: string - name: evolution_type dtype: string - name: metadata dtype: string - name: episode_done dtype: bool - name: question dtype: string - name: ground_truth dtype: string splits: - name: korean_v1 num_bytes: 30243 num_examples: 10 download_size: 0 dataset_size: 30243 configs: - config_name: default data_files: - split: korean_v1 path: data/korean_v1-* --- # Dataset Card for "ragas-test-dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
Arjuna17/lepala-ai-swahili-hausa-dataset	Arjuna17	"2025-03-01T07:11:27Z"	0	[ "license:apache-2.0", "region:us" ]	null	"2025-03-01T07:11:27Z"	--- license: apache-2.0 ---
Yuanxin-Liu/test_yx_noanswer-math_gsm-gemma-1.1-7b-it-iter_sample_7500_temp_1.0_gen_10_mlr5e-5	Yuanxin-Liu	"2025-03-01T07:19:22Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:19:20Z"	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: rational_answer dtype: string splits: - name: train num_bytes: 5409009 num_examples: 5802 download_size: 2877131 dataset_size: 5409009 configs: - config_name: default data_files: - split: train path: data/train-* ---
mangopy/ToolRet-before-sample	mangopy	"2025-03-01T07:39:53Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:25:37Z"	--- dataset_info: - config_name: apibank features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 189985 num_examples: 101 download_size: 45023 dataset_size: 189985 - config_name: apigen features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 991447 num_examples: 1000 download_size: 352171 dataset_size: 991447 - config_name: appbench features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2302790 num_examples: 801 download_size: 167561 dataset_size: 2302790 - config_name: autotools-food features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 783804 num_examples: 41 download_size: 138180 dataset_size: 783804 - config_name: autotools-music features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 8965195 num_examples: 50 download_size: 1884066 dataset_size: 8965195 - config_name: autotools-weather features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2171417 num_examples: 50 download_size: 369274 dataset_size: 2171417 - config_name: craft-math-algebra features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 328289 num_examples: 280 download_size: 119720 dataset_size: 328289 - config_name: craft-tabmwp features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 293350 num_examples: 174 download_size: 93220 dataset_size: 293350 - config_name: craft-vqa features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 270344 num_examples: 200 download_size: 85397 dataset_size: 270344 - config_name: gorilla-huggingface features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 831939 num_examples: 500 download_size: 290310 dataset_size: 831939 - config_name: gorilla-pytorch features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 295446 num_examples: 186 download_size: 43369 dataset_size: 295446 - config_name: gorilla-tensor features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 837843 num_examples: 688 download_size: 62197 dataset_size: 837843 - config_name: gpt4tools features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1607837 num_examples: 1727 download_size: 305122 dataset_size: 1607837 - config_name: gta features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 19979 num_examples: 14 download_size: 18173 dataset_size: 19979 - config_name: metatool features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2122091 num_examples: 5327 download_size: 516864 dataset_size: 2122091 - config_name: mnms features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 4932111 num_examples: 6874 download_size: 1411357 dataset_size: 4932111 - config_name: restgpt-spotify features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1764116 num_examples: 57 download_size: 292932 dataset_size: 1764116 - config_name: restgpt-tmdb features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 3540877 num_examples: 100 download_size: 1100630 dataset_size: 3540877 - config_name: reversechain features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 348064 num_examples: 200 download_size: 100619 dataset_size: 348064 - config_name: rotbench features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 488460 num_examples: 550 download_size: 92990 dataset_size: 488460 - config_name: t-eval-dialog features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 5585569 num_examples: 2660 download_size: 531217 dataset_size: 5585569 - config_name: t-eval-step features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1248324 num_examples: 553 download_size: 207806 dataset_size: 1248324 - config_name: taskbench-daily features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 5062303 num_examples: 4320 download_size: 838455 dataset_size: 5062303 - config_name: taskbench-huggingface features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 9117645 num_examples: 7546 download_size: 1489433 dataset_size: 9117645 - config_name: taskbench-multimedia features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 5191129 num_examples: 5584 download_size: 987374 dataset_size: 5191129 - config_name: tool-be-honest features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 466852 num_examples: 350 download_size: 166352 dataset_size: 466852 - config_name: toolace features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1498462 num_examples: 1000 download_size: 618326 dataset_size: 1498462 - config_name: toolalpaca features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 91909 num_examples: 94 download_size: 36261 dataset_size: 91909 - config_name: toolbench features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2808494 num_examples: 1100 download_size: 922485 dataset_size: 2808494 - config_name: toolbench-sam features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 340762 num_examples: 387 download_size: 31793 dataset_size: 340762 - config_name: toolemu features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1501848 num_examples: 144 download_size: 175104 dataset_size: 1501848 - config_name: tooleyes features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 335319 num_examples: 382 download_size: 58939 dataset_size: 335319 - config_name: toolink features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 562007 num_examples: 497 download_size: 114950 dataset_size: 562007 - config_name: toollens features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 45444525 num_examples: 18770 download_size: 1642020 dataset_size: 45444525 - config_name: ultratool features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 763581 num_examples: 500 download_size: 134582 dataset_size: 763581 configs: - config_name: apibank data_files: - split: queries path: apibank/queries-* - config_name: apigen data_files: - split: queries path: apigen/queries-* - config_name: appbench data_files: - split: queries path: appbench/queries-* - config_name: autotools-food data_files: - split: queries path: autotools-food/queries-* - config_name: autotools-music data_files: - split: queries path: autotools-music/queries-* - config_name: autotools-weather data_files: - split: queries path: autotools-weather/queries-* - config_name: craft-math-algebra data_files: - split: queries path: craft-math-algebra/queries-* - config_name: craft-tabmwp data_files: - split: queries path: craft-tabmwp/queries-* - config_name: craft-vqa data_files: - split: queries path: craft-vqa/queries-* - config_name: gorilla-huggingface data_files: - split: queries path: gorilla-huggingface/queries-* - config_name: gorilla-pytorch data_files: - split: queries path: gorilla-pytorch/queries-* - config_name: gorilla-tensor data_files: - split: queries path: gorilla-tensor/queries-* - config_name: gpt4tools data_files: - split: queries path: gpt4tools/queries-* - config_name: gta data_files: - split: queries path: gta/queries-* - config_name: metatool data_files: - split: queries path: metatool/queries-* - config_name: mnms data_files: - split: queries path: mnms/queries-* - config_name: restgpt-spotify data_files: - split: queries path: restgpt-spotify/queries-* - config_name: restgpt-tmdb data_files: - split: queries path: restgpt-tmdb/queries-* - config_name: reversechain data_files: - split: queries path: reversechain/queries-* - config_name: rotbench data_files: - split: queries path: rotbench/queries-* - config_name: t-eval-dialog data_files: - split: queries path: t-eval-dialog/queries-* - config_name: t-eval-step data_files: - split: queries path: t-eval-step/queries-* - config_name: taskbench-daily data_files: - split: queries path: taskbench-daily/queries-* - config_name: taskbench-huggingface data_files: - split: queries path: taskbench-huggingface/queries-* - config_name: taskbench-multimedia data_files: - split: queries path: taskbench-multimedia/queries-* - config_name: tool-be-honest data_files: - split: queries path: tool-be-honest/queries-* - config_name: toolace data_files: - split: queries path: toolace/queries-* - config_name: toolalpaca data_files: - split: queries path: toolalpaca/queries-* - config_name: toolbench data_files: - split: queries path: toolbench/queries-* - config_name: toolbench-sam data_files: - split: queries path: toolbench-sam/queries-* - config_name: toolemu data_files: - split: queries path: toolemu/queries-* - config_name: tooleyes data_files: - split: queries path: tooleyes/queries-* - config_name: toolink data_files: - split: queries path: toolink/queries-* - config_name: toollens data_files: - split: queries path: toollens/queries-* - config_name: ultratool data_files: - split: queries path: ultratool/queries-* --- 🔧 Retrieving useful tools from a large-scale toolset is an important step for Large language model (LLMs) in tool learning. This project (ToolRet) contribute to (i) _the first comprehensive tool retrieval benchmark_ to systematically evaluate existing information retrieval (IR) models on tool retrieval tasks; and (ii) a large-scale training dataset to optimize the expertise of IR models on this tool retrieval task. Our evaluation benchmark `ToolRet` is built by first collecting existing datasets and efficiently sample diverse retrieval tasks from them through K-means. This `ToolRet-before-sample` contains all raw datasets before K-means while the final version (after sampling) is released on [ToolRet](https://huggingface.co/datasets/mangopy/ToolRet-Tools).
akhooli/arabicweb24filtered	akhooli	"2025-03-01T08:21:23Z"	0	[ "size_categories:10M<n<100M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:27:43Z"	--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 126409415256.64795 num_examples: 25394308 download_size: 60382553275 dataset_size: 126409415256.64795 configs: - config_name: default data_files: - split: train path: data/train-* ---
jinchenliuljc/FinSum	jinchenliuljc	"2025-03-01T09:43:36Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:48:35Z"	--- dataset_info: features: - name: text dtype: string - name: summary dtype: string - name: source dtype: string splits: - name: train num_bytes: 137444134 num_examples: 2305 - name: test num_bytes: 45668551 num_examples: 577 download_size: 88451041 dataset_size: 183112685 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
brunopbb/ufcg-labmet-fala-texto-main	brunopbb	"2025-03-01T07:49:37Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:49:20Z"	--- dataset_info: features: - name: id dtype: string - name: audio dtype: audio - name: transcription dtype: string splits: - name: train num_bytes: 98985053.0 num_examples: 507 - name: test num_bytes: 30899581.0 num_examples: 159 download_size: 126897890 dataset_size: 129884634.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
Yuanxin-Liu/test_yx_noanswer-math_gsm-gemma-2-9b-it-iter_sample_7500_temp_1.0_gen_10_mlr5e-5	Yuanxin-Liu	"2025-03-01T07:50:05Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:50:03Z"	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: rational_answer dtype: string splits: - name: train num_bytes: 6658223 num_examples: 6818 download_size: 3504453 dataset_size: 6658223 configs: - config_name: default data_files: - split: train path: data/train-* ---
keikhosrotav/tools-images	keikhosrotav	"2025-03-01T13:10:14Z"	0	[ "license:mit", "region:us" ]	null	"2025-03-01T07:53:17Z"	--- license: mit ---
fluff269/brainweb-ipp-train	fluff269	"2025-03-01T07:58:27Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:55:00Z"	--- dataset_info: features: - name: original_prompt dtype: string - name: original_image dtype: image - name: edit_prompt dtype: string - name: edited_prompt dtype: string - name: edited_image dtype: image splits: - name: train num_bytes: 1899382435.56 num_examples: 3620 download_size: 1898608370 dataset_size: 1899382435.56 configs: - config_name: default data_files: - split: train path: data/train-* ---
abhiakshat/testing_dataset	abhiakshat	"2025-03-01T07:58:29Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T07:58:25Z"	--- dataset_info: features: - name: file_name dtype: string - name: content dtype: string splits: - name: train num_bytes: 5183861 num_examples: 30 download_size: 1782569 dataset_size: 5183861 configs: - config_name: default data_files: - split: train path: data/train-* ---
FlippyDora/numia_prompt_reward_iter2_0-10000	FlippyDora	"2025-03-01T08:03:13Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:03:10Z"	--- dataset_info: features: - name: prompt dtype: string - name: responses sequence: string - name: gt dtype: string - name: problem dtype: string - name: rewards sequence: float64 splits: - name: train num_bytes: 215121274 num_examples: 10000 download_size: 82762031 dataset_size: 215121274 configs: - config_name: default data_files: - split: train path: data/train-* ---
Johnson111788/OpenImages_3DSR_feb27_unique_1k	Johnson111788	"2025-03-01T08:09:23Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:09:21Z"	--- dataset_info: features: - name: index dtype: string - name: question dtype: string - name: A dtype: string - name: B dtype: string - name: C dtype: string - name: D dtype: string - name: bounding_box list: - name: bbox_3d sequence: float64 - name: label dtype: string - name: direction list: - name: front_dir sequence: float64 - name: label dtype: string - name: left_dir sequence: float64 - name: answer dtype: string - name: answer_cot dtype: string - name: answer_name dtype: string - name: category dtype: string - name: image_url dtype: string splits: - name: train num_bytes: 1332953 num_examples: 792 - name: val num_bytes: 340836 num_examples: 204 download_size: 432413 dataset_size: 1673789 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* ---
lookas/astra_grab_floor_toys_base_cmd_pos	lookas	"2025-03-01T08:13:30Z"	0	[ "task_categories:robotics", "license:apache-2.0", "size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us", "LeRobot", "astra" ]	[ "robotics" ]	"2025-03-01T08:11:28Z"	--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - astra configs: - config_name: default data_files: data//.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - Homepage: [More Information Needed] - Paper: [More Information Needed] - License: apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": null, "total_episodes": 50, "total_frames": 73944, "total_tasks": 1, "total_videos": 150, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "action": { "dtype": "float32", "shape": [ 18 ], "names": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ] }, "observation.state": { "dtype": "float32", "shape": [ 18 ], "names": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ] }, "action.arm_l": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "action.gripper_l": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "action.arm_r": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "action.gripper_r": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "action.base": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "action.eef_l": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "action.eef_r": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "action.head": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1 ] }, "observation.state.arm_l": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "observation.state.gripper_l": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "observation.state.arm_r": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "observation.state.gripper_r": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "observation.state.base": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "observation.state.eef_l": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "observation.state.eef_r": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "observation.state.odom": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "observation.state.head": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1 ] }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "observation.images.head": { "dtype": "video", "shape": [ 360, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 360, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.wrist_left": { "dtype": "video", "shape": [ 360, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 360, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.wrist_right": { "dtype": "video", "shape": [ 360, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 360, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } } } } ``` ## Citation BibTeX: ```bibtex [More Information Needed] ```
Yuanxin-Liu/test_yx_answer-math_gsm-gemma-2-9b-it-iter_sample_7500_temp_1.0_gen_10_mlr5e-5	Yuanxin-Liu	"2025-03-01T08:14:25Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:14:24Z"	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: rational_answer dtype: string splits: - name: train num_bytes: 6776189 num_examples: 6818 download_size: 3541819 dataset_size: 6776189 configs: - config_name: default data_files: - split: train path: data/train-* ---
SecondComming/style_transfer_testset	SecondComming	"2025-03-01T08:17:01Z"	0	[ "license:mit", "size_categories:n<1K", "format:imagefolder", "modality:image", "library:datasets", "library:mlcroissant", "region:us" ]	null	"2025-03-01T08:14:36Z"	--- license: mit ---
adalbertojunior/gsm8k-portuguese	adalbertojunior	"2025-03-01T08:14:51Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:14:47Z"	--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: train num_bytes: 4334482 num_examples: 7473 - name: test num_bytes: 781310 num_examples: 1319 download_size: 2960234 dataset_size: 5115792 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
kngrg/wikifacts-sents-v2	kngrg	"2025-03-01T11:38:22Z"	0	[ "language:ru", "license:mit", "size_categories:1M<n<10M", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:19:46Z"	--- license: mit language: - ru configs: - config_name: corpus data_files: - corpus.jsonl - config_name: queries data_files: - queries.jsonl ---
kngrg/wikifacts-sents-v2-qrels	kngrg	"2025-03-01T10:27:44Z"	0	[ "language:ru", "license:mit", "size_categories:10K<n<100K", "format:csv", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:20:01Z"	--- license: mit language: - ru configs: - config_name: qrels data_files: - split: dev path: dev.tsv ---
friedrichor/DiDeMo	friedrichor	"2025-03-01T18:17:38Z"	0	[ "task_categories:text-to-video", "task_categories:text-retrieval", "task_categories:video-classification", "language:en", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	[ "text-to-video", "text-retrieval", "video-classification" ]	"2025-03-01T08:21:37Z"	--- configs: - config_name: default data_files: - split: train path: "didemo_train.json" - split: test path: "didemo_test.json" task_categories: - text-to-video - text-retrieval - video-classification language: - en size_categories: - 10K<n<100K --- [DiDeMo](https://openaccess.thecvf.com/content_iccv_2017/html/Hendricks_Localizing_Moments_in_ICCV_2017_paper.html) contains 10K long-form videos from Flickr. For each video, ~4 short sentences are annotated in temporal order. We follow the existing works to concatenate those short sentences and evaluate ‘paragraph-to-video’ retrieval on this benchmark. We adopt the official split: - Train: 8,395 videos, 8,395 captions (concatenate from 33,005 captions) - Val: 1,065 videos, 1,065 captions (concatenate from 4,290 captions) (We don't have the collection yet.) - Test: 1,004 videos, 1,004 captions (concatenate from 4,021 captions) --- Video Release: [DiDeMoRelease](https://data.ciirc.cvut.cz/public/projects/LisaAnne/DiDeMoRelease/)
sobiswriter/my-distiset-59f766b1	sobiswriter	"2025-03-01T08:33:28Z"	0	[ "task_categories:text-classification", "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "library:distilabel", "region:us", "synthetic", "distilabel", "rlaif", "datacraft" ]	[ "text-classification" ]	"2025-03-01T08:33:26Z"	--- size_categories: n<1K task_categories: - text-classification dataset_info: features: - name: text dtype: string - name: labels sequence: class_label: names: '0': average '1': low '2': efficient splits: - name: train num_bytes: 42680 num_examples: 85 download_size: 24094 dataset_size: 42680 configs: - config_name: default data_files: - split: train path: data/train-* tags: - synthetic - distilabel - rlaif - datacraft --- <p align="left"> <a href="https://github.com/argilla-io/distilabel"> <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/> </a> </p> # Dataset Card for my-distiset-59f766b1 This dataset has been created with [distilabel](https://distilabel.argilla.io/). ## Dataset Summary This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI: ```console distilabel pipeline run --config "https://huggingface.co/datasets/sobiswriter/my-distiset-59f766b1/raw/main/pipeline.yaml" ``` or explore the configuration: ```console distilabel pipeline info --config "https://huggingface.co/datasets/sobiswriter/my-distiset-59f766b1/raw/main/pipeline.yaml" ``` ## Dataset structure The examples have the following structure per configuration: <details><summary> Configuration: default </summary><hr> ```json { "labels": [ 0, 1, 2 ], "text": "Assuming a mid-size sedan vehicle with an estimated city cycle fuel economy of 35 miles per gallon, driven by a 45-year-old male with a moderate driving style under typical weather conditions with average temperatures between 65\u00b0F to 75\u00b0F\u0027, the classification of the vehicle\u0027s fuel efficiency must consider multiple variables, including the driver\u0027s idling behavior, starting habits, speed adherence, and driving route choice." } ``` This subset can be loaded as: ```python from datasets import load_dataset ds = load_dataset("sobiswriter/my-distiset-59f766b1", "default") ``` Or simply as it follows, since there's only one configuration and is named `default`: ```python from datasets import load_dataset ds = load_dataset("sobiswriter/my-distiset-59f766b1") ``` </details>
DariaaaS/characters_dataset1	DariaaaS	"2025-03-01T08:42:42Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:42:39Z"	--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 32712.82608695652 num_examples: 83 - name: test num_bytes: 3547.1739130434785 num_examples: 9 download_size: 21797 dataset_size: 36260.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
infinite-dataset-hub/EventPhotographySnapshot	infinite-dataset-hub	"2025-03-01T08:43:34Z"	0	[ "license:mit", "size_categories:n<1K", "format:csv", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "infinite-dataset-hub", "synthetic" ]	null	"2025-03-01T08:43:33Z"	--- license: mit tags: - infinite-dataset-hub - synthetic --- # EventPhotographySnapshot tags: event, lighting, ML-task:Classification _Note: This is an AI-generated dataset so its content may be inaccurate or false_ Dataset Description: The 'EventPhotographySnapshot' dataset is a curated collection of textual descriptions of various event photography scenarios. Each entry provides a snapshot description and includes contextual details relevant to the lighting conditions, key subjects, and actions occurring within the image. This dataset aims to serve as a rich training ground for machine learning models focused on the classification of event photography based on composition, lighting, and other stylistic features. CSV Content Preview: ```csv "ID","Snippet","Label" "001","During the grand opening of the theater, a spotlight illuminates the stage, casting dramatic shadows.","Highlight" "002","A wedding reception's picturesque sunset, guests in festive attire against a backdrop of azure sky.","Wedding" "003","A dimly lit jazz club with a single spotlight shining on a saxophonist in mid-note.","Jazz Club" "004","A child's laughter echoes as they play with colorful balloons in a sunlit playground.","Children's Play" "005","Banquet hall during a banquet, the elegant table setting reflects the chandelier's soft glow.","Banquet" ``` The labels such as 'Highlight', 'Wedding', 'Jazz Club', 'Children's Play', and 'Banquet' are illustrative categories for classification tasks in event photography. The textual snippets provide context to machine learning models for understanding and classifying images based on their photographic content. Source of the data: The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'photography': - Dataset Generation Page: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=photography&dataset=EventPhotographySnapshot&tags=event,+lighting,+ML-task:Classification - Model: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct - More Datasets: https://huggingface.co/datasets?other=infinite-dataset-hub
Chand0320/fsd50k_test	Chand0320	"2025-03-01T08:50:46Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:50:44Z"	--- dataset_info: features: - name: audio sequence: int16 - name: sampling_rate dtype: int64 - name: id dtype: string - name: labels dtype: string splits: - name: train num_bytes: 22466493 num_examples: 20 download_size: 21078138 dataset_size: 22466493 configs: - config_name: default data_files: - split: train path: data/train-* ---
Tagiyevff/tradings	Tagiyevff	"2025-03-01T08:52:04Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:51:22Z"	--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: response dtype: string splits: - name: train num_bytes: 39345.7476635514 num_examples: 149 - name: test num_bytes: 17164.252336448597 num_examples: 65 download_size: 14149 dataset_size: 56510.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
PhoenixZ/MM-AlignBench	PhoenixZ	"2025-03-01T09:21:14Z"	2	[ "arxiv:2502.18411", "region:us" ]	null	"2025-03-01T08:54:40Z"	--- dataset_info: features: - name: index dtype: string - name: question dtype: string - name: type dtype: string - name: claude3_sonnet dtype: string - name: image dtype: image - name: gt dtype: string splits: - name: test num_bytes: 26873033.0 num_examples: 252 download_size: 26095029 dataset_size: 26873033.0 --- ## Introduction Paper: [Paper](https://arxiv.org/abs/2502.18411), Github: [Github](https://github.com/PhoenixZ810/OmniAlign-V), Page: [Page](https://phoenixz810.github.io/OmniAlign-V/), SFT Dataset: [OmniAlign-V](https://huggingface.co/datasets/PhoenixZ/OmniAlign-V), DPO Dataset: [OmniAlign-V-DPO](https://huggingface.co/datasets/PhoenixZ/OmniAlign-V-DPO), MM-AlignBench is a benchmark designed to evaluate how well MLLMs align with human preferences. It consists of 252 high-quality, human-annotated samples , featuring diverse image types and open-ended questions. Inspired by Arena-style benchmarks, it employs: - GPT-4o as the judge model for scoring responses. - Claude-Sonnet-3 as the reference model for comparison. MM-AlignBench is now integrated into [VLMEvalkit](https://github.com/open-compass/VLMEvalKit), an open-source evaluation toolkit that supports over 200 MLLMs. You can quickly evaluate your model using the following steps: ``` git clone https://github.com/open-compass/VLMEvalKit.git cd VLMEvalKit pip install -e . python run.py --model MODEL_NAME --data MMAlignBench ``` For more details on VLMEvalKit , please refer to its [repository](https://github.com/open-compass/VLMEvalKit) ## LeaderBoard Below are the results of state-of-the-art MLLMs evaluated on MM-AlignBench : \| Model \| Win Rate \| Reward \| Better+ \| Better \| Tie \| Worse \| Worse+ \| \|-------------------------------\|------------------------------\|---------------------------\|------------\|-----\|----\|-----\|-----\| \| Claude3.5V-Sonnet \| 84.9 \| +51.4 \| 70 \| 144 \| 13 \| 25 \| 0 \| \| GPT-4o \| 81.3 \| +49.0 \| 81 \| 124 \| 12 \| 31 \| 4 \| \| GPT-4V \| 82.5 \| +46.0 \| 57 \| 151 \| 12 \| 31 \| 1 \| \| GeminiFlash1.5-002 \| 77.0 \| +39.1 \| 56 \| 138 \| 14 \| 35 \| 9 \| \| LLaVANext-OA-32B-DPO \| 74.2 \| +36.9 \| 49 \| 138 \| 20 \| 40 \| 5 \| \| Qwen2VL-72B \| 61.5 \| +21.6 \| 43 \| 112 \| 15 \| 75 \| 7 \| \| LLaVANext-OA-32B \| 62.3 \| +19.4 \| 31 \| 126 \| 19 \| 62 \| 14 \| \| Claude-3V-Sonnet \| 50 \| 0 \| - \| - \| - \| - \| - \| \| Qwen2VL-7B \| 44.4 \| -5.8 \| 28 \| 84 \| 5 \| 101 \| 34 \| \| InternVL2-72B \| 44.4 \| -6.9 \| 19 \| 93 \| 8 \| 98 \| 34 \| \| InternVL2-8B-MPO \| 40.1 \| -10.9 \| 26 \| 75 \| 10 \| 100 \| 41 \| \| InternVL2-8B \| 31.3 \| -21.8 \| 18 \| 61 \| 15 \| 109 \| 49 \| \| LLaMA3.2-Vision-11B \| 27.8 \| -33.7 \| 18 \| 52 \| 4 \| 98 \| 80 \| \| LLaVANext-Qwen32B \| 26.6 \| -29.0 \| 16 \| 51 \| 10 \| 121 \| 54 \| \| LLaVA-OneVision-7B \| 23.8 \| -46.2 \| 14 \| 46 \| 1 \| 75 \| 116 \| \| MiniCPM-V-2.5 \| 12.7 \| -53.0 \| 9 \| 23 \| 8 \| 116 \| 96 \| \| Xcomposer2.5-7B \| 7.5 \| -74.0 \| 5 \| 14 \| 3 \| 63 \| 167 \| \| Idefics3-8B \| 2.7 \| -92.3 \| 3 \| 4 \| 0 \| 15 \| 230 \|
dz237/finetuning_demo	dz237	"2025-03-01T08:54:58Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T08:54:56Z"	--- dataset_info: features: - name: prompt dtype: string splits: - name: train num_bytes: 107640 num_examples: 100 download_size: 33627 dataset_size: 107640 configs: - config_name: default data_files: - split: train path: data/train-* ---
svjack/Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned	svjack	"2025-03-01T12:09:17Z"	0	[ "size_categories:1K<n<10K", "modality:text", "modality:video", "library:datasets", "library:mlcroissant", "region:us" ]	null	"2025-03-01T08:58:38Z"	--- configs: - config_name: default data_files: - split: train path: - ".mp4" - "metadata.csv" --- - In the style of Yae Miko , The video opens with a darkened scene where the details are not clearly visible. As the video progresses, the lighting improves, revealing a character dressed in traditional Japanese attire, standing on a stone pathway. The character is holding what appears to be a scroll or a piece of paper. Surrounding the character are several lanterns with intricate designs, casting a warm glow on the pathway and the character's clothing. In the background, there is a traditional Japanese building with red pillars and a tiled roof, partially obscured by cherry blossom trees in full bloom. The blossoms are pink and create a soft contrast against the night sky. The ground is covered with fallen petals, adding to the serene and picturesque setting. <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/tDDH_W8-iBY74bbay9WUX.mp4"></video> Reorganized version of [`Wild-Heart/Disney-VideoGeneration-Dataset`](https://huggingface.co/datasets/Wild-Heart/Disney-VideoGeneration-Dataset). This is needed for [Mochi-1 fine-tuning](https://github.com/genmoai/mochi/tree/aba74c1b5e0755b1fa3343d9e4bd22e89de77ab1/demos/fine_tuner). ```bash sudo apt-get update && sudo apt-get install cbm ffmpeg git-lfs pip install moviepy==1.0.3 opencv-python git clone https://huggingface.co/datasets/svjack/Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned git clone https://huggingface.co/datasets/svjack/genshin_impact_YAE_MIKO_images_and_styled_captions ``` ```python import os import cv2 import numpy as np from moviepy.editor import VideoFileClip from tqdm import tqdm import shutil def change_resolution_and_save(input_path, output_path, target_width=1024, target_height=768, max_duration=4): """处理图片和视频分辨率，添加黑边并分段处理视频""" os.makedirs(output_path, exist_ok=True) for root, dirs, files in os.walk(input_path): for file in tqdm(files, desc="Processing files"): file_path = os.path.join(root, file) relative_path = os.path.relpath(file_path, input_path) output_dir = os.path.dirname(os.path.join(output_path, relative_path)) # 处理图片 if file.lower().endswith(('.png', '.jpg', '.jpeg')): try: # 原图片处理逻辑 img = cv2.imread(file_path) h, w = img.shape[:2] scale = min(target_width / w, target_height / h) new_w = int(w scale) new_h = int(h * scale) resized_img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA) background = np.zeros((target_height, target_width, 3), dtype=np.uint8) x_offset = (target_width - new_w) // 2 y_offset = (target_height - new_h) // 2 background[y_offset:y_offset+new_h, x_offset:x_offset+new_w] = resized_img output_file_path = os.path.join(output_path, relative_path) os.makedirs(os.path.dirname(output_file_path), exist_ok=True) cv2.imwrite(output_file_path, background) # 处理对应的txt文件 base_name = os.path.splitext(file)[0] txt_source = os.path.join(root, f"{base_name}.txt") if os.path.exists(txt_source): txt_target = os.path.join(output_dir, f"{base_name}.txt") shutil.copy2(txt_source, txt_target) except Exception as e: print(f"图片处理失败 {file_path}: {e}") # 处理视频 elif file.lower().endswith('.mp4'): try: clip = VideoFileClip(file_path) total_duration = clip.duration num_segments = int(total_duration // max_duration) # 处理每个分段 for i in range(num_segments): start_time = i * max_duration end_time = min((i+1) * max_duration, total_duration) sub_clip = clip.subclip(start_time, end_time) # 构造分段文件名 base_name = os.path.splitext(file)[0] output_filename = f"{base_name}_{i}.mp4" output_file_path = os.path.join(output_dir, output_filename) os.makedirs(os.path.dirname(output_file_path), exist_ok=True) # 处理视频帧 def process_frame(frame): img = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) h, w = img.shape[:2] scale = min(target_width / w, target_height / h) new_w = int(w * scale) new_h = int(h * scale) resized_img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA) background = np.zeros((target_height, target_width, 3), dtype=np.uint8) x_offset = (target_width - new_w) // 2 y_offset = (target_height - new_h) // 2 background[y_offset:y_offset+new_h, x_offset:x_offset+new_w] = resized_img return cv2.cvtColor(background, cv2.COLOR_BGR2RGB) processed_clip = sub_clip.fl_image(process_frame) fps = processed_clip.fps if processed_clip.fps else 24 # 写入处理后的视频 processed_clip.write_videofile( output_file_path, codec='libx264', fps=fps, preset='slow', threads=4, audio=False ) processed_clip.close() # 处理对应的txt文件 txt_source = os.path.join(root, f"{base_name}.txt") if os.path.exists(txt_source): txt_target = os.path.join(output_dir, f"{base_name}_{i}.txt") shutil.copy2(txt_source, txt_target) clip.close() except Exception as e: print(f"视频处理失败 {file_path}: {e}") # 使用示例 change_resolution_and_save( input_path="Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned", output_path="Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned_512x384x1", target_width=512, target_height=384, max_duration=1 ) ''' change_resolution_and_save( input_path="genshin_impact_YAE_MIKO_images_and_styled_captions", output_path="genshin_impact_YAE_MIKO_images_and_styled_captions_1024x768x4", target_width=1024, target_height=768, max_duration=4 ) ''' ``` ```bash mkdir -p dataset/train cp Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned_512x384x1/.mp4 dataset/train cp Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned_512x384x1/.txt dataset/train cp genshin_impact_YAE_MIKO_images_and_styled_captions/.png dataset/train cp genshin_impact_YAE_MIKO_images_and_styled_captions/.txt dataset/train ```
DariaaaS/characters_dataset_no_tokens	DariaaaS	"2025-03-01T09:06:22Z"	0	[ "region:us" ]	null	"2025-03-01T09:06:19Z"	--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 27898.82608695652 num_examples: 83 - name: test num_bytes: 3025.1739130434785 num_examples: 9 download_size: 20093 dataset_size: 30924.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
wangjl1512/so100_test	wangjl1512	"2025-03-01T11:00:44Z"	0	[ "task_categories:robotics", "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us", "LeRobot", "so100", "tutorial" ]	[ "robotics" ]	"2025-03-01T09:11:39Z"	--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - so100 - tutorial configs: - config_name: default data_files: data//.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - Homepage: [More Information Needed] - Paper: [More Information Needed] - License: apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 1, "total_frames": 196, "total_tasks": 1, "total_videos": 1, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.images.laptop": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation BibTeX: ```bibtex [More Information Needed] ```
Chand0320/fsd50k_test2	Chand0320	"2025-03-01T09:15:14Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:13:55Z"	--- dataset_info: features: - name: audio dtype: audio - name: id dtype: int64 - name: labels dtype: string splits: - name: train num_bytes: 22467864.0 num_examples: 20 download_size: 20743253 dataset_size: 22467864.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
NGMOB/distill_psychology-10k-r1.json	NGMOB	"2025-03-01T09:17:26Z"	0	[ "license:cc", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:16:27Z"	--- license: cc ---
avrecum/r1_llama3_8b_activation_patched_outputs_2048	avrecum	"2025-03-01T09:18:09Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:18:06Z"	--- dataset_info: features: - name: question dtype: string - name: patched_output sequence: string - name: unpatched_output sequence: string splits: - name: train num_bytes: 552019 num_examples: 50 download_size: 223629 dataset_size: 552019 configs: - config_name: default data_files: - split: train path: data/train-* ---
tensorlink-dev/PTN-BTC-v2	tensorlink-dev	"2025-03-01T09:22:51Z"	0	[ "size_categories:100K<n<1M", "format:parquet", "modality:tabular", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:20:21Z"	--- dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: volume dtype: float64 - name: vwap dtype: float64 - name: open dtype: float64 - name: close dtype: float64 - name: high dtype: float64 - name: low dtype: float64 - name: date dtype: timestamp[ns] - name: number_of_trades dtype: int64 - name: future_return dtype: float64 - name: atr dtype: float64 - name: rr-6 dtype: float64 - name: rr-12 dtype: float64 - name: rr-36 dtype: float64 - name: rr-144 dtype: float64 - name: rr-288 dtype: float64 - name: log_return dtype: float64 - name: simple_return dtype: float64 - name: cumulative_return dtype: float64 - name: volatility dtype: float64 - name: momentum dtype: float64 - name: zscore_price dtype: float64 - name: price_diff dtype: float64 - name: high_low_range dtype: float64 - name: open_close_range dtype: float64 - name: volume_change dtype: float64 - name: relative_volume dtype: float64 - name: volume_rolling_mean dtype: float64 - name: volume_rolling_std dtype: float64 - name: volume_zscore dtype: float64 - name: volume_surge dtype: float64 - name: price_range_vs_volume dtype: float64 - name: price_change dtype: float64 - name: price_volume_corr dtype: float64 - name: momentum_vs_volume dtype: float64 - name: log_return_vs_volume dtype: float64 - name: upper_wick dtype: float64 - name: lower_wick dtype: float64 - name: wick_ratio dtype: float64 - name: wick_vs_volume dtype: float64 - name: body_to_range_ratio dtype: float64 - name: open_close_ratio dtype: float64 - name: timestamp dtype: timestamp[ns] - name: hour dtype: int32 - name: minute dtype: int32 - name: hour_sin dtype: float64 - name: hour_cos dtype: float64 - name: minute_sin dtype: float64 - name: minute_cos dtype: float64 - name: hour_weighted_relative_volume dtype: float64 - name: minute_weighted_relative_volume dtype: float64 - name: hour_weighted_momentum dtype: float64 - name: minute_weighted_momentum dtype: float64 - name: hour_weighted_volatility dtype: float64 - name: minute_weighted_volatility dtype: float64 - name: hour_weighted_simple_return dtype: float64 - name: minute_weighted_simple_return dtype: float64 - name: hour_weighted_volume_zscore dtype: float64 - name: minute_weighted_volume_zscore dtype: float64 - name: hour_weighted_high_low_range dtype: float64 - name: minute_weighted_high_low_range dtype: float64 - name: hour_weighted_high dtype: float64 - name: minute_weighted_high dtype: float64 - name: hour_weighted_low dtype: float64 - name: minute_weighted_low dtype: float64 - name: hour_weighted_open dtype: float64 - name: minute_weighted_open dtype: float64 - name: hour_weighted_close dtype: float64 - name: minute_weighted_close dtype: float64 - name: hour_weighted_volume_change dtype: float64 - name: minute_weighted_volume_change dtype: float64 - name: hour_weighted_upper_wick dtype: float64 - name: minute_weighted_upper_wick dtype: float64 - name: hour_weighted_lower_wick dtype: float64 - name: minute_weighted_lower_wick dtype: float64 - name: hour_weighted_wick_ratio dtype: float64 - name: minute_weighted_wick_ratio dtype: float64 - name: hour_weighted_wick_vs_volume dtype: float64 - name: minute_weighted_wick_vs_volume dtype: float64 - name: hour_weighted_body_to_range_ratio dtype: float64 - name: minute_weighted_body_to_range_ratio dtype: float64 - name: hour_weighted_open_close_ratio dtype: float64 - name: minute_weighted_open_close_ratio dtype: float64 - name: log_return-12-mean dtype: float64 - name: log_return-12-diff dtype: float64 - name: log_return-36-mean dtype: float64 - name: log_return-36-diff dtype: float64 - name: log_return-144-mean dtype: float64 - name: log_return-144-diff dtype: float64 - name: log_return-288-mean dtype: float64 - name: log_return-288-diff dtype: float64 - name: log_return-864-mean dtype: float64 - name: log_return-864-diff dtype: float64 - name: simple_return-12-mean dtype: float64 - name: simple_return-12-diff dtype: float64 - name: simple_return-36-mean dtype: float64 - name: simple_return-36-diff dtype: float64 - name: simple_return-144-mean dtype: float64 - name: simple_return-144-diff dtype: float64 - name: simple_return-288-mean dtype: float64 - name: simple_return-288-diff dtype: float64 - name: simple_return-864-mean dtype: float64 - name: simple_return-864-diff dtype: float64 - name: cumulative_return-12-mean dtype: float64 - name: cumulative_return-12-diff dtype: float64 - name: cumulative_return-36-mean dtype: float64 - name: cumulative_return-36-diff dtype: float64 - name: cumulative_return-144-mean dtype: float64 - name: cumulative_return-144-diff dtype: float64 - name: cumulative_return-288-mean dtype: float64 - name: cumulative_return-288-diff dtype: float64 - name: cumulative_return-864-mean dtype: float64 - name: cumulative_return-864-diff dtype: float64 - name: volatility-12-mean dtype: float64 - name: volatility-12-diff dtype: float64 - name: volatility-36-mean dtype: float64 - name: volatility-36-diff dtype: float64 - name: volatility-144-mean dtype: float64 - name: volatility-144-diff dtype: float64 - name: volatility-288-mean dtype: float64 - name: volatility-288-diff dtype: float64 - name: volatility-864-mean dtype: float64 - name: volatility-864-diff dtype: float64 - name: momentum-12-mean dtype: float64 - name: momentum-12-diff dtype: float64 - name: momentum-36-mean dtype: float64 - name: momentum-36-diff dtype: float64 - name: momentum-144-mean dtype: float64 - name: momentum-144-diff dtype: float64 - name: momentum-288-mean dtype: float64 - name: momentum-288-diff dtype: float64 - name: momentum-864-mean dtype: float64 - name: momentum-864-diff dtype: float64 - name: zscore_price-12-mean dtype: float64 - name: zscore_price-12-diff dtype: float64 - name: zscore_price-36-mean dtype: float64 - name: zscore_price-36-diff dtype: float64 - name: zscore_price-144-mean dtype: float64 - name: zscore_price-144-diff dtype: float64 - name: zscore_price-288-mean dtype: float64 - name: zscore_price-288-diff dtype: float64 - name: zscore_price-864-mean dtype: float64 - name: zscore_price-864-diff dtype: float64 - name: price_diff-12-mean dtype: float64 - name: price_diff-12-diff dtype: float64 - name: price_diff-36-mean dtype: float64 - name: price_diff-36-diff dtype: float64 - name: price_diff-144-mean dtype: float64 - name: price_diff-144-diff dtype: float64 - name: price_diff-288-mean dtype: float64 - name: price_diff-288-diff dtype: float64 - name: price_diff-864-mean dtype: float64 - name: price_diff-864-diff dtype: float64 - name: high_low_range-12-mean dtype: float64 - name: high_low_range-12-diff dtype: float64 - name: high_low_range-36-mean dtype: float64 - name: high_low_range-36-diff dtype: float64 - name: high_low_range-144-mean dtype: float64 - name: high_low_range-144-diff dtype: float64 - name: high_low_range-288-mean dtype: float64 - name: high_low_range-288-diff dtype: float64 - 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name: minute_weighted_lower_wick-144-mean dtype: float64 - name: minute_weighted_lower_wick-144-diff dtype: float64 - name: minute_weighted_lower_wick-288-mean dtype: float64 - name: minute_weighted_lower_wick-288-diff dtype: float64 - name: minute_weighted_lower_wick-864-mean dtype: float64 - name: minute_weighted_lower_wick-864-diff dtype: float64 - name: hour_weighted_wick_ratio-12-mean dtype: float64 - name: hour_weighted_wick_ratio-12-diff dtype: float64 - name: hour_weighted_wick_ratio-36-mean dtype: float64 - name: hour_weighted_wick_ratio-36-diff dtype: float64 - name: hour_weighted_wick_ratio-144-mean dtype: float64 - name: hour_weighted_wick_ratio-144-diff dtype: float64 - name: hour_weighted_wick_ratio-288-mean dtype: float64 - name: hour_weighted_wick_ratio-288-diff dtype: float64 - name: hour_weighted_wick_ratio-864-mean dtype: float64 - name: hour_weighted_wick_ratio-864-diff dtype: float64 - name: minute_weighted_wick_ratio-12-mean dtype: float64 - name: minute_weighted_wick_ratio-12-diff dtype: float64 - name: minute_weighted_wick_ratio-36-mean dtype: float64 - name: minute_weighted_wick_ratio-36-diff dtype: float64 - name: minute_weighted_wick_ratio-144-mean dtype: float64 - name: minute_weighted_wick_ratio-144-diff dtype: float64 - name: minute_weighted_wick_ratio-288-mean dtype: float64 - name: minute_weighted_wick_ratio-288-diff dtype: float64 - name: minute_weighted_wick_ratio-864-mean dtype: float64 - name: minute_weighted_wick_ratio-864-diff dtype: float64 - name: hour_weighted_wick_vs_volume-12-mean dtype: float64 - name: hour_weighted_wick_vs_volume-12-diff dtype: float64 - name: hour_weighted_wick_vs_volume-36-mean dtype: float64 - name: hour_weighted_wick_vs_volume-36-diff dtype: float64 - name: hour_weighted_wick_vs_volume-144-mean dtype: float64 - name: hour_weighted_wick_vs_volume-144-diff dtype: float64 - name: hour_weighted_wick_vs_volume-288-mean dtype: float64 - name: hour_weighted_wick_vs_volume-288-diff dtype: float64 - name: hour_weighted_wick_vs_volume-864-mean dtype: float64 - name: hour_weighted_wick_vs_volume-864-diff dtype: float64 - name: minute_weighted_wick_vs_volume-12-mean dtype: float64 - name: minute_weighted_wick_vs_volume-12-diff dtype: float64 - name: minute_weighted_wick_vs_volume-36-mean dtype: float64 - name: minute_weighted_wick_vs_volume-36-diff dtype: float64 - name: minute_weighted_wick_vs_volume-144-mean dtype: float64 - name: minute_weighted_wick_vs_volume-144-diff dtype: float64 - name: minute_weighted_wick_vs_volume-288-mean dtype: float64 - name: minute_weighted_wick_vs_volume-288-diff dtype: float64 - name: minute_weighted_wick_vs_volume-864-mean dtype: float64 - name: minute_weighted_wick_vs_volume-864-diff dtype: float64 - name: hour_weighted_body_to_range_ratio-12-mean dtype: float64 - name: hour_weighted_body_to_range_ratio-12-diff dtype: float64 - name: hour_weighted_body_to_range_ratio-36-mean dtype: float64 - name: hour_weighted_body_to_range_ratio-36-diff dtype: float64 - name: hour_weighted_body_to_range_ratio-144-mean dtype: float64 - name: hour_weighted_body_to_range_ratio-144-diff dtype: float64 - name: hour_weighted_body_to_range_ratio-288-mean dtype: float64 - name: hour_weighted_body_to_range_ratio-288-diff dtype: float64 - name: hour_weighted_body_to_range_ratio-864-mean dtype: float64 - name: hour_weighted_body_to_range_ratio-864-diff dtype: float64 - name: minute_weighted_body_to_range_ratio-12-mean dtype: float64 - name: minute_weighted_body_to_range_ratio-12-diff dtype: float64 - name: minute_weighted_body_to_range_ratio-36-mean dtype: float64 - name: minute_weighted_body_to_range_ratio-36-diff dtype: float64 - name: minute_weighted_body_to_range_ratio-144-mean dtype: float64 - name: minute_weighted_body_to_range_ratio-144-diff dtype: float64 - name: minute_weighted_body_to_range_ratio-288-mean dtype: float64 - name: minute_weighted_body_to_range_ratio-288-diff dtype: float64 - name: minute_weighted_body_to_range_ratio-864-mean dtype: float64 - name: minute_weighted_body_to_range_ratio-864-diff dtype: float64 - name: hour_weighted_open_close_ratio-12-mean dtype: float64 - name: hour_weighted_open_close_ratio-12-diff dtype: float64 - name: hour_weighted_open_close_ratio-36-mean dtype: float64 - name: hour_weighted_open_close_ratio-36-diff dtype: float64 - name: hour_weighted_open_close_ratio-144-mean dtype: float64 - name: hour_weighted_open_close_ratio-144-diff dtype: float64 - name: hour_weighted_open_close_ratio-288-mean dtype: float64 - name: hour_weighted_open_close_ratio-288-diff dtype: float64 - name: hour_weighted_open_close_ratio-864-mean dtype: float64 - name: hour_weighted_open_close_ratio-864-diff dtype: float64 - name: minute_weighted_open_close_ratio-12-mean dtype: float64 - name: minute_weighted_open_close_ratio-12-diff dtype: float64 - name: minute_weighted_open_close_ratio-36-mean dtype: float64 - name: minute_weighted_open_close_ratio-36-diff dtype: float64 - name: minute_weighted_open_close_ratio-144-mean dtype: float64 - name: minute_weighted_open_close_ratio-144-diff dtype: float64 - name: minute_weighted_open_close_ratio-288-mean dtype: float64 - name: minute_weighted_open_close_ratio-288-diff dtype: float64 - name: minute_weighted_open_close_ratio-864-mean dtype: float64 - name: minute_weighted_open_close_ratio-864-diff dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1783200000 num_examples: 300000 - name: test num_bytes: 761283744 num_examples: 128076 download_size: 2762518533 dataset_size: 2544483744 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
hgissbkh/ner	hgissbkh	"2025-03-01T09:22:54Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:22:36Z"	--- dataset_info: features: - name: words sequence: string - name: ner sequence: class_label: names: '0': O '1': B-PER '2': I-PER '3': B-ORG '4': I-ORG '5': B-LOC '6': I-LOC '7': B-MISC '8': I-MISC - name: lang dtype: string splits: - name: train num_bytes: 3530082 num_examples: 14042 - name: validation num_bytes: 3397847 num_examples: 10944 - name: test num_bytes: 3848249 num_examples: 13186 download_size: 2573896 dataset_size: 10776178 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
hgissbkh/pos	hgissbkh	"2025-03-01T09:23:16Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:23:03Z"	--- dataset_info: features: - name: words sequence: string - name: pos sequence: class_label: names: '0': ADJ '1': ADP '2': ADV '3': AUX '4': CCONJ '5': DET '6': INTJ '7': NOUN '8': NUM '9': PART '10': PRON '11': PROPN '12': PUNCT '13': SCONJ '14': SYM '15': VERB '16': X - name: lang dtype: string splits: - name: train num_bytes: 7431679 num_examples: 25376 - name: validation num_bytes: 1488674 num_examples: 4915 - name: test num_bytes: 1130096 num_examples: 4072 download_size: 2275692 dataset_size: 10050449 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---
HKUSTAudio/VidMuse-V2M-Dataset	HKUSTAudio	"2025-03-01T09:39:03Z"	0	[ "license:cc-by-nc-4.0", "size_categories:100K<n<1M", "format:text", "modality:text", "library:datasets", "library:mlcroissant", "arxiv:2406.04321", "region:us" ]	null	"2025-03-01T09:24:00Z"	--- license: cc-by-nc-4.0 --- # V2M Dataset: A Large-Scale Video-to-Music Dataset 🎶 The V2M dataset is proposed in the [VidMuse project](https://vidmuse.github.io/), aimed at advancing research in video-to-music generation. ## ✨ Dataset Overview The V2M dataset comprises 360K pairs of videos and music, covering various types including movie trailers, advertisements, and documentaries. This dataset provides researchers with a rich resource to explore the relationship between video content and music generation. ## 🛠️ Usage Instructions - Download the dataset: ```bash git clone https://huggingface.co/datasets/HKUSTAudio/VidMuse-V2M-Dataset ``` - Dataset structure: ``` V2M/ ├── V2M.txt ├── V2M-20k.txt └── V2M-bench.txt ``` ## 🎯 Citation If you use the V2M dataset in your research, please consider citing: ``` @article{tian2024vidmuse, title={Vidmuse: A simple video-to-music generation framework with long-short-term modeling}, author={Tian, Zeyue and Liu, Zhaoyang and Yuan, Ruibin and Pan, Jiahao and Liu, Qifeng and Tan, Xu and Chen, Qifeng and Xue, Wei and Guo, Yike}, journal={arXiv preprint arXiv:2406.04321}, year={2024} } ```
LauKramer/learn_hf_food_not_food_image_captions	LauKramer	"2025-03-01T09:25:07Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:25:06Z"	--- dataset_info: features: - name: text dtype: string - name: label dtype: string splits: - name: train num_bytes: 20253 num_examples: 250 download_size: 11617 dataset_size: 20253 configs: - config_name: default data_files: - split: train path: data/train-* ---
notewee/drivethruthailand-labeled	notewee	"2025-03-01T11:59:15Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:image", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:25:24Z"	--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: file_name dtype: string - name: image dtype: binary - name: video_id dtype: string - name: frame_number dtype: int64 - name: timestamp dtype: float64 - name: road_type dtype: string - name: weather dtype: string - name: scene dtype: string - name: has_car dtype: int64 - name: has_motorcycle dtype: int64 - name: has_truck dtype: int64 - name: has_bus dtype: int64 - name: has_pedestrian dtype: int64 - name: has_bicycle dtype: int64 - name: has_traffic_light dtype: int64 - name: has_traffic_sign dtype: int64 splits: - name: train num_bytes: 129850347 num_examples: 107 download_size: 129818832 dataset_size: 129850347 --- # DriveThruThailand Labeled Dataset ## Dataset Description A collection of 107 screenshots from DriveThruThailand videos with labels. ### Features Each image includes the following features: - file_name: File name - image_path: Path to the image within the dataset - video_id: Source video ID - frame_number: Frame number in the source video - timestamp: Timestamp in seconds - road_type: Road type classification (highway, urban) - weather: Weather condition (clear, cloudy) - scene: Scene type (city, countryside) ### File Structure - `/images/`: Contains all the images - `metadata.csv`: Contains metadata for all images ### Usage This dataset can be used with Hugging Face's `datasets` library: ```python from datasets import load_dataset # Load the dataset dataset = load_dataset("notewee/drivethruthailand-labeled") # Access metadata metadata = pd.read_csv(dataset["metadata.csv"]) # Access images image_paths = metadata["image_path"].tolist() ``` ## License CC-BY-4.0
haesleinhuepf/SlightInsight_Cache	haesleinhuepf	"2025-03-01T13:00:42Z"	0	[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "modality:timeseries", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:34:01Z"	--- dataset_info: features: - name: key dtype: string - name: zenodo_record_id dtype: string - name: zenodo_filename dtype: string - name: page_number dtype: int64 - name: text sequence: float32 - name: visual sequence: float64 - name: mixed sequence: float32 splits: - name: train num_bytes: 32425773 num_examples: 2617 download_size: 34100658 dataset_size: 32425773 configs: - config_name: default data_files: - split: train path: data/train-* ---
DariaaaS/characters_csv	DariaaaS	"2025-03-01T09:35:54Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:34:31Z"	--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 25512.695652173912 num_examples: 82 - name: test num_bytes: 3111.304347826087 num_examples: 10 download_size: 22263 dataset_size: 28624.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---
Chan-Y/full-311k	Chan-Y	"2025-03-01T10:02:32Z"	0	[ "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:38:44Z"	--- dataset_info: features: - name: question dtype: string - name: thinking dtype: string - name: answer dtype: string splits: - name: train num_bytes: 2968707254 num_examples: 311713 download_size: 1348665307 dataset_size: 2968707254 configs: - config_name: default data_files: - split: train path: data/train-* ---
yadunund/so100_test	yadunund	"2025-03-01T09:39:14Z"	0	[ "task_categories:robotics", "license:apache-2.0", "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "LeRobot", "so100", "tutorial" ]	[ "robotics" ]	"2025-03-01T09:39:11Z"	--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - so100 - tutorial configs: - config_name: default data_files: data//.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - Homepage: [More Information Needed] - Paper: [More Information Needed] - License: apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 1, "total_frames": 150, "total_tasks": 1, "total_videos": 1, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.images.camera": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation BibTeX: ```bibtex [More Information Needed] ```
ayushayush591/cross_lingual	ayushayush591	"2025-03-01T09:45:11Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:45:09Z"	--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: validation num_bytes: 71317.62 num_examples: 99 download_size: 50109 dataset_size: 71317.62 configs: - config_name: default data_files: - split: validation path: data/validation-* ---
Mohamed-DLM/asr_en_ar_switch_split_117_final_updated	Mohamed-DLM	"2025-03-01T09:58:57Z"	0	[ "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:47:55Z"	--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: transcription dtype: string splits: - name: train num_bytes: 5410674.0 num_examples: 57 download_size: 4813550 dataset_size: 5410674.0 configs: - config_name: default data_files: - split: train path: data/train-* ---
H1tak3/phishing-html-tokenized	H1tak3	"2025-03-01T09:59:48Z"	0	[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T09:59:44Z"	--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels dtype: int64 splits: - name: train num_bytes: 26674480 num_examples: 10355 - name: validation num_bytes: 6671840 num_examples: 2590 download_size: 8349661 dataset_size: 33346320 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---
g-ronimo/IN1k256-AR-buckets-latents_dc-ae-f32c32-sana-1.0	g-ronimo	"2025-03-01T15:22:18Z"	0	[ "size_categories:1M<n<10M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]	null	"2025-03-01T10:03:38Z"	--- dataset_info: features: - name: label dtype: string - name: latent sequence: sequence: sequence: sequence: float32 configs: - config_name: default data_files: - split: train path: data/train_* - split: validation path: data/validation_* - split: train_AR_4_to_3 path: data/train_AR_4_to_3.* - split: train_AR_3_to_4 path: data/train_AR_3_to_4.* - split: train_AR_1_to_1 path: data/train_AR_1_to_1.* - split: validation_AR_4_to_3 path: data/validation_AR_4_to_3.* - split: validation_AR_3_to_4 path: data/validation_AR_3_to_4.* - split: validation_AR_1_to_1 path: data/validation_AR_1_to_1.* ---

tuandunghcmut/sp_bilingual_ds

tuandunghcmut

"2024-09-04T09:59:04Z"

0

[ "size_categories:1M<n<10M", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-09-04T08:33:31Z"

--- dataset_info: features: - name: image_name dtype: string - name: person_id dtype: int64 - name: caption_0 dtype: string - name: caption_1 dtype: string - name: attributes dtype: string - name: prompt_caption dtype: string - name: image dtype: image - name: viet_captions sequence: string - name: viet_prompt_caption sequence: string splits: - name: train num_bytes: 54940531595.615 num_examples: 4791127 download_size: 51005008832 dataset_size: 54940531595.615 configs: - config_name: default data_files: - split: train path: data/train-* ---

QuanHoangNgoc/EVJ_NonCluster

QuanHoangNgoc

"2024-10-22T04:18:28Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-10-22T04:12:29Z"

--- dataset_info: features: - name: answer dtype: string - name: image dtype: image - name: prompt dtype: string splits: - name: train num_bytes: 1101443348.656 num_examples: 7748 - name: test num_bytes: 89786903.0 num_examples: 567 download_size: 3546373791 dataset_size: 1191230251.656 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

QuanHoangNgoc/EVJ_Cluster

QuanHoangNgoc

"2024-10-22T13:55:58Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-10-22T13:55:09Z"

--- dataset_info: features: - name: answer dtype: string - name: cluster dtype: int32 - name: image dtype: image - name: prompt dtype: string splits: - name: train num_bytes: 965568274.42 num_examples: 5820 - name: test num_bytes: 358795481.815 num_examples: 2495 download_size: 1239772291 dataset_size: 1324363756.235 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

QuanHoangNgoc/EVJ_Cluster-Normal

QuanHoangNgoc

"2024-10-23T09:19:34Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-10-23T09:18:39Z"

--- dataset_info: features: - name: answer dtype: string - name: cluster dtype: int32 - name: image dtype: image - name: prompt dtype: string splits: - name: li_train num_bytes: 900073595.5 num_examples: 5820 - name: li_test num_bytes: 354791631.125 num_examples: 2495 download_size: 1239073417 dataset_size: 1254865226.625 configs: - config_name: default data_files: - split: li_train path: data/li_train-* - split: li_test path: data/li_test-* ---

ayyuce/drugs

ayyuce

"2024-11-06T23:31:49Z"

0

[ "license:mit", "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-11-06T23:30:48Z"

--- license: mit ---

QuanHoangNgoc/EVJ_Cluster-Expanded

QuanHoangNgoc

"2024-11-13T14:19:21Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-11-13T14:16:49Z"

--- dataset_info: features: - name: answer dtype: string - name: cluster dtype: int32 - name: image dtype: image - name: prompt dtype: string - name: description dtype: string splits: - name: li_train num_bytes: 901224571.5 num_examples: 5820 - name: li_test num_bytes: 355286984.125 num_examples: 2495 download_size: 1239503465 dataset_size: 1256511555.625 configs: - config_name: default data_files: - split: li_train path: data/li_train-* - split: li_test path: data/li_test-* ---

shroom-semeval25/hallucinated_answer_generated_dataset_cleaned

shroom-semeval25

"2024-11-13T22:39:51Z"

0

[ "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-11-13T22:34:17Z"

--- dataset_info: features: - name: id dtype: string - name: title dtype: string - name: context dtype: string - name: question dtype: string - name: answers struct: - name: answer_start sequence: int32 - name: text sequence: string - name: correct_answer_generated dtype: string - name: hallucinated_answer_generated dtype: string splits: - name: train num_bytes: 397086774 num_examples: 373848 - name: validation num_bytes: 49601442 num_examples: 46731 - name: test num_bytes: 49545525 num_examples: 46732 download_size: 319248685 dataset_size: 496233741 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

QuanHoangNgoc/MS_TestSet_5k

QuanHoangNgoc

"2024-12-27T06:56:58Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2024-12-27T06:55:30Z"

--- dataset_info: features: - name: image dtype: image - name: caption sequence: string splits: - name: test num_bytes: 2417550920.0 num_examples: 5000 download_size: 2417029684 dataset_size: 2417550920.0 configs: - config_name: default data_files: - split: test path: data/test-* ---

kevin017/tokenized_bioS_QA_b_city_large

kevin017

"2025-02-28T07:22:57Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-01-09T20:17:56Z"

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87638953 num_examples: 34061 - name: test num_bytes: 87641526 num_examples: 34062 download_size: 12501009 dataset_size: 175280479 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

kevin017/tokenized_bioS_QA_b_date_large

kevin017

"2025-02-28T07:23:07Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-01-09T20:18:05Z"

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87690413 num_examples: 34081 - name: test num_bytes: 87664683 num_examples: 34071 download_size: 13740130 dataset_size: 175355096 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

kevin017/tokenized_bioS_QA_c_city_large

kevin017

"2025-02-28T07:23:17Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-01-09T20:18:15Z"

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87170667 num_examples: 33879 - name: test num_bytes: 87165521 num_examples: 33877 download_size: 10015228 dataset_size: 174336188 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

kevin017/tokenized_bioS_QA_c_name_large

kevin017

"2025-02-28T07:23:28Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-01-09T20:18:22Z"

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87232419 num_examples: 33903 - name: test num_bytes: 87214408 num_examples: 33896 download_size: 12468376 dataset_size: 174446827 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

kevin017/tokenized_bioS_QA_univ_large

kevin017

"2025-02-28T07:23:49Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-01-09T20:18:39Z"

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 splits: - name: train num_bytes: 87353350 num_examples: 33950 - name: test num_bytes: 87343058 num_examples: 33946 download_size: 13016656 dataset_size: 174696408 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

QuanHoangNgoc/MS-Flickr30k

QuanHoangNgoc

"2025-01-19T03:36:29Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-01-19T03:31:54Z"

--- dataset_info: features: - name: image dtype: image - name: caption dtype: string splits: - name: test num_bytes: 6740690168.25 num_examples: 36014 download_size: 6721561298 dataset_size: 6740690168.25 configs: - config_name: default data_files: - split: test path: data/test-* ---

roomtour3d/Self-Critic-Hallucination_withGT

roomtour3d

"2025-02-25T07:09:15Z"

0

[ "license:mit", "size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-02-25T06:51:38Z"

--- license: mit dataset_info: features: - name: ds_name dtype: string - name: image dtype: image - name: question dtype: string - name: chosen dtype: string - name: rejected dtype: string - name: origin_dataset dtype: string - name: origin_split dtype: string - name: idx dtype: string - name: image_path dtype: string - name: gt list: - name: answer dtype: string - name: answer_id dtype: int64 splits: - name: train num_bytes: 4414647639.4 num_examples: 28696 download_size: 4391984529 dataset_size: 4414647639.4 configs: - config_name: default data_files: - split: train path: data/train-* ---

inkoziev/ArsPoetica

inkoziev

"2025-03-01T04:38:37Z"

0

1

[ "task_categories:text-generation", "language:ru", "license:cc-by-4.0", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "poetry" ]

[ "text-generation" ]

"2025-02-27T16:28:19Z"

--- license: cc-by-4.0 task_categories: - text-generation language: - ru tags: - poetry pretty_name: Ars Poetica size_categories: - 1K<n<10K --- # Ars Poetica The **Ars Poetica** dataset is a collection of Russian-language poetry from the 19th and 20th centuries, annotated with stress marks. This dataset is designed to support research in generative poetry, computational linguistics, and related fields. Stress marks were automatically assigned using the [RussianPoetryScansionTool](https://github.com/Koziev/RussianPoetryScansionTool) library. While the dataset has undergone selective manual validation, users should be aware of potential inaccuracies due to the automated process. ## Example ``` За́йку бро́сила хозя́йка — Под дождё́м оста́лся за́йка. Со скаме́йки сле́зть не мо́г, Ве́сь до ни́точки промо́к. ``` ## Citing If you use this dataset in your research or projects, please cite it as follows: ```bibtex @misc{Conversations, author = {Ilya Koziev}, title = {Ars Poetica Dataset}, year = {2025}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/datasets/inkoziev/ArsPoetica}}, } ``` ## License This dataset is licensed under the [CC-BY-NC-4.0](https://creativecommons.org/licenses/by-nc/4.0/) license, which permits non-commercial use only. For commercial use, please contact the author at [inkoziev@gmail.com]. By using this dataset, you agree to: - Provide proper attribution to the author. - Refrain from using the dataset for commercial purposes without explicit permission. ## Other resources If you are interested in stress placement and homograph resolution, check out our [Homograph Resolution Evaluation Dataset](https://huggingface.co/datasets/inkoziev/HomographResolutionEval) and [Rifma](https://github.com/Koziev/Rifma) datasets. ## Limitations - **Automated Processing**: The dataset was generated through automated methods with only selective manual validation. As a result, some poems may contain misspellings, typos, or other imperfections. - **Limited Scope**: The dataset does not encompass the full range of Russian poetic works. Many genres, forms, and longer compositions are excluded, making it unsuitable as a comprehensive anthology of Russian poetry.

caitwong/balanced_translation_dataset4

caitwong

"2025-03-01T17:49:51Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-02-28T10:42:27Z"

--- dataset_info: - config_name: batch_1 features: - name: None dtype: string - name: en dtype: string - name: vi dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 - name: th dtype: string - name: conversation_id dtype: string - name: category dtype: string - name: zh dtype: string - name: hi dtype: string - name: ms dtype: string splits: - name: train num_bytes: 2470346 num_examples: 5654 download_size: 1201569 dataset_size: 2470346 - config_name: batch_2 features: - name: en dtype: string - name: tl dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 - name: conversation_id dtype: string - name: category dtype: string - name: zh dtype: string - name: id dtype: string splits: - name: train num_bytes: 2192989 num_examples: 3222 download_size: 1213459 dataset_size: 2192989 - config_name: batch_3 features: - name: en dtype: string - name: id dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 splits: - name: train num_bytes: 1254295 num_examples: 5072 download_size: 803079 dataset_size: 1254295 - config_name: batch_4 features: - name: None dtype: string - name: en dtype: string - name: vi dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 - name: conversation_id dtype: string - name: category dtype: string - name: zh dtype: string - name: th dtype: string splits: - name: train num_bytes: 6529648 num_examples: 8992 download_size: 3312547 dataset_size: 6529648 - config_name: batch_5 features: - name: tl dtype: string - name: en dtype: string - name: source_file dtype: string - name: target_lang dtype: string - name: idx dtype: int64 splits: - name: train num_bytes: 2627409 num_examples: 3137 download_size: 1475207 dataset_size: 2627409 configs: - config_name: batch_1 data_files: - split: train path: batch_1/train-* - config_name: batch_2 data_files: - split: train path: batch_2/train-* - config_name: batch_3 data_files: - split: train path: batch_3/train-* - config_name: batch_4 data_files: - split: train path: batch_4/train-* - config_name: batch_5 data_files: - split: train path: batch_5/train-* ---

simwit/medmoe-vqa-rad

simwit

"2025-03-01T07:52:46Z"

0

[ "license:apache-2.0", "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-02-28T10:50:55Z"

--- license: apache-2.0 dataset_info: features: - name: image dtype: image - name: question dtype: string - name: answer dtype: string - name: modality dtype: string - name: answer_type dtype: string splits: - name: test_all num_bytes: 23826356.0 num_examples: 451 - name: test_open num_bytes: 9281911.0 num_examples: 179 - name: test_closed num_bytes: 14544445.0 num_examples: 272 download_size: 26472530 dataset_size: 47652712.0 configs: - config_name: default data_files: - split: test_all path: data/test_all-* - split: test_open path: data/test_open-* - split: test_closed path: data/test_closed-* ---

g-ronimo/IN1k256-AR-buckets-latents_dc-ae-f32c32-sana-1.0_

g-ronimo

"2025-02-28T19:54:06Z"

0

[ "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-02-28T17:52:21Z"

--- dataset_info: features: - name: label dtype: string - name: latent sequence: sequence: sequence: sequence: float32 splits: - name: train_AR_4_to_3.part_0 num_bytes: 1144094328 num_examples: 100000 - name: train_AR_4_to_3.part_1 num_bytes: 1144088430 num_examples: 100000 - name: train_AR_3_to_4.part_0 num_bytes: 1169764996 num_examples: 100000 - name: train_AR_4_to_3.part_2 num_bytes: 1144091474 num_examples: 100000 download_size: 1573133511 dataset_size: 4602039228 configs: - config_name: default data_files: - split: train_AR_4_to_3.part_0 path: data/train_AR_4_to_3.part_0-* - split: train_AR_4_to_3.part_1 path: data/train_AR_4_to_3.part_1-* - split: train_AR_3_to_4.part_0 path: data/train_AR_3_to_4.part_0-* - split: train_AR_4_to_3.part_2 path: data/train_AR_4_to_3.part_2-* ---

yvngexe/data_generated_by_armo

yvngexe

"2025-03-01T14:18:28Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-02-28T23:26:25Z"

--- dataset_info: features: - name: prompt_id dtype: string - name: prompt dtype: string - name: response_0 dtype: string - name: response_1 dtype: string - name: response_2 dtype: string - name: response_3 dtype: string - name: response_4 dtype: string - name: response_0_reward dtype: float64 - name: response_1_reward dtype: float64 - name: response_2_reward dtype: float64 - name: response_3_reward dtype: float64 - name: response_4_reward dtype: float64 splits: - name: train num_bytes: 591568112 num_examples: 61814 download_size: 319605004 dataset_size: 591568112 configs: - config_name: default data_files: - split: train path: data/train-* ---

ZStack-AI/LongDPO_openqa

ZStack-AI

"2025-03-01T04:45:14Z"

0

[ "license:apache-2.0", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "region:us" ]

null

"2025-03-01T03:41:58Z"

--- license: apache-2.0 ---

inkoziev/HomographResolutionEval

inkoziev

"2025-03-01T04:32:49Z"

0

1

[ "task_categories:text2text-generation", "language:ru", "license:cc-by-4.0", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "homograph_resolution", "accentuation" ]

[ "text2text-generation" ]

"2025-03-01T04:14:23Z"

--- license: cc-by-4.0 task_categories: - text2text-generation language: - ru tags: - homograph_resolution - accentuation pretty_name: Homograph Resulution Evaluation Dataset size_categories: - 1K<n<10K --- # Homograph Resolution Evaluation Dataset This dataset is designed to evaluate the performance of Text-to-Speech (TTS) systems and Language Models (LLMs) in resolving homographs in the Russian language. It contains carefully curated sentences, each featuring at least one homograph with the correct stress indicated. The dataset is particularly useful for assessing stress assignment tasks in TTS systems and LLMs. ## Key Features - **Language**: Russian - **Focus**: Homograph resolution and stress assignment - **Unique Samples**: All sentences are original and highly unlikely to be present in existing training datasets. - **Stress Annotation**: Correct stress marks are provided for homographs, enabling precise evaluation. ## Dataset Fields - `context`: A sentence containing one or more homographs. - `homograph`: The homograph with the correct stress mark. - `accentuated_context`: The full sentence with correct stress marks applied. **Note**: When evaluating, stress marks on words other than the homograph can be ignored. ## Limitations 1. **Single Stress Variant**: Each sample provides only one stress variant for a homograph, even if the homograph appears multiple times in the sentence (though such cases are rare). 2. **Limited Homograph Coverage**: The dataset includes a small subset of homographs in the Russian language and is not exhaustive. ## Intended Use This dataset is ideal for: - Evaluating TTS systems on homograph resolution and stress assignment. - Benchmarking LLMs on their ability to handle ambiguous linguistic constructs. - Research in computational linguistics, particularly in stress disambiguation and homograph resolution. ## Citing the Dataset If you use this dataset in your research or projects, please cite it as follows: ```bibtex @misc{HomographResolutionEval, author = {Ilya Koziev}, title = {Homograph Resolution Evaluation Dataset}, year = {2025}, publisher = {Hugging Face}, howpublished = {\url{https://huggingface.co/datasets/inkoziev/HomographResolutionEval}} }

RyanYr/simpleRLZero_matheval

RyanYr

"2025-03-01T04:21:24Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T04:21:23Z"

--- dataset_info: features: - name: data_source dtype: string - name: problem dtype: string - name: solution dtype: string - name: answer dtype: string - name: prompt list: - name: content dtype: string - name: role dtype: string - name: reward_model struct: - name: ground_truth dtype: string - name: style dtype: string - name: responses dtype: string - name: gt_ans dtype: string - name: extracted_solution dtype: string - name: rm_scores dtype: bool splits: - name: train num_bytes: 6208004 num_examples: 1517 download_size: 2469747 dataset_size: 6208004 configs: - config_name: default data_files: - split: train path: data/train-* ---

introvoyz041/Lilac

introvoyz041

"2025-03-01T04:34:24Z"

0

[ "license:apache-2.0", "region:us" ]

null

"2025-03-01T04:34:00Z"

--- license: apache-2.0 ---

RyanYr/RLHFlowOnlineDPOPPOZero_matheval

RyanYr

"2025-03-01T04:34:28Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T04:34:26Z"

--- dataset_info: features: - name: data_source dtype: string - name: problem dtype: string - name: solution dtype: string - name: answer dtype: string - name: prompt list: - name: content dtype: string - name: role dtype: string - name: reward_model struct: - name: ground_truth dtype: string - name: style dtype: string - name: responses dtype: string - name: gt_ans dtype: string - name: extracted_solution dtype: string - name: rm_scores dtype: bool splits: - name: train num_bytes: 5914469 num_examples: 1517 download_size: 2481535 dataset_size: 5914469 configs: - config_name: default data_files: - split: train path: data/train-* ---

introvoyz041/Llm4sd

introvoyz041

"2025-03-01T04:41:48Z"

0

[ "license:apache-2.0", "size_categories:10K<n<100K", "format:text", "modality:text", "library:datasets", "library:mlcroissant", "region:us" ]

null

"2025-03-01T04:41:28Z"

--- license: apache-2.0 ---

RyanYr/Qwen2.5-7B-DPO-Zero_matheval

RyanYr

"2025-03-01T04:47:45Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T04:47:44Z"

--- dataset_info: features: - name: data_source dtype: string - name: problem dtype: string - name: solution dtype: string - name: answer dtype: string - name: prompt list: - name: content dtype: string - name: role dtype: string - name: reward_model struct: - name: ground_truth dtype: string - name: style dtype: string - name: responses dtype: string - name: gt_ans dtype: string - name: extracted_solution dtype: string - name: rm_scores dtype: bool splits: - name: train num_bytes: 7259615 num_examples: 1517 download_size: 2543503 dataset_size: 7259615 configs: - config_name: default data_files: - split: train path: data/train-* ---

meowterspace42/gretel-dd-glue-wnli

meowterspace42

"2025-03-01T07:18:31Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T04:53:41Z"

--- dataset_info: features: - name: seed_examples dtype: string - name: writing_style dtype: string - name: domain dtype: string - name: target_label dtype: string - name: glue_example dtype: string - name: eval_metrics dtype: string splits: - name: train num_bytes: 1743260 num_examples: 1798 download_size: 203981 dataset_size: 1743260 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/test_1

Isylimanov099

"2025-03-01T05:00:44Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:00:42Z"

--- dataset_info: features: - name: Description dtype: string - name: Client dtype: string - name: Lawyer dtype: string splits: - name: train num_bytes: 88010 num_examples: 100 download_size: 36369 dataset_size: 88010 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/FAInAselmOon

Isylimanov099

"2025-03-01T05:01:37Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:01:35Z"

--- dataset_info: features: - name: Описание dtype: float64 - name: Вопрос dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 3062 num_examples: 13 download_size: 4077 dataset_size: 3062 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/Test-books

Isylimanov099

"2025-03-01T05:05:14Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:05:10Z"

--- dataset_info: features: - name: Описание dtype: string - name: Вопрос dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 7866 num_examples: 29 download_size: 7873 dataset_size: 7866 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/kamila09

Isylimanov099

"2025-03-01T05:05:18Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:05:16Z"

--- dataset_info: features: - name: Описание dtype: string - name: Вопросы dtype: string - name: Ответы dtype: string splits: - name: train num_bytes: 8603 num_examples: 50 download_size: 6236 dataset_size: 8603 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/Koala

Isylimanov099

"2025-03-01T05:05:25Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:05:23Z"

--- dataset_info: features: - name: Описание dtype: string - name: Вопрос dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 16480 num_examples: 43 download_size: 10197 dataset_size: 16480 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/Travel

Isylimanov099

"2025-03-01T05:06:35Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:06:32Z"

--- dataset_info: features: - name: 'Unnamed: 0' dtype: float64 - name: 描述 dtype: string - name: 问题 dtype: string - name: 回答 dtype: string splits: - name: train num_bytes: 9557 num_examples: 16 download_size: 9231 dataset_size: 9557 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/IT-Venera

Isylimanov099

"2025-03-01T05:08:30Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:08:25Z"

--- dataset_info: features: - name: 'Unnamed: 0' dtype: string - name: 'Unnamed: 1' dtype: string - name: 'Unnamed: 2' dtype: string - name: 'Unnamed: 3' dtype: string splits: - name: train num_bytes: 66500 num_examples: 75 download_size: 28823 dataset_size: 66500 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/a.bolotbekovvvna

Isylimanov099

"2025-03-01T05:08:35Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:08:33Z"

--- dataset_info: features: - name: ОПИСАНИЕ dtype: string - name: ВОПРОС dtype: string - name: ОТВЕТ dtype: string splits: - name: train num_bytes: 7046 num_examples: 20 download_size: 6608 dataset_size: 7046 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/asel

Isylimanov099

"2025-03-01T05:12:05Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:12:02Z"

--- dataset_info: features: - name: Описание dtype: string - name: Вопросы dtype: string - name: Ответ dtype: string splits: - name: train num_bytes: 1516 num_examples: 4 download_size: 3866 dataset_size: 1516 configs: - config_name: default data_files: - split: train path: data/train-* ---

Isylimanov099/JanybekovaAijamal

Isylimanov099

"2025-03-01T05:20:32Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T05:20:30Z"

--- dataset_info: features: - name: Описание dtype: string - name: Вопрос dtype: string - name: Ответ dtype: float64 - name: 'Unnamed: 3' dtype: float64 - name: Кв. 3 dtype: float64 - name: Кв. 4 dtype: float64 splits: - name: train num_bytes: 20168 num_examples: 277 download_size: 6889 dataset_size: 20168 configs: - config_name: default data_files: - split: train path: data/train-* ---

jmhb/VidDiffBench

jmhb

"2025-03-01T08:23:54Z"

0

1

[ "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "modality:video", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "video" ]

null

"2025-03-01T06:08:38Z"

--- tags: - video dataset_info: features: - name: sample_key dtype: string - name: vid0_thumbnail dtype: image - name: vid1_thumbnail dtype: image - name: videos dtype: string - name: action dtype: string - name: action_name dtype: string - name: action_description dtype: string - name: source_dataset dtype: string - name: sample_hash dtype: int64 - name: retrieval_frames dtype: string - name: differences_annotated dtype: string - name: differences_gt dtype: string - name: domain dtype: string - name: split dtype: string - name: n_differences_open_prediction dtype: int64 splits: - name: test num_bytes: 15219230.154398564 num_examples: 549 download_size: 6445835 dataset_size: 15219230.154398564 configs: - config_name: default data_files: - split: test path: data/test-* --- # Dataset card for "VidDiffBench" This is the dataset / benchmark for [Video Action Differencing](https://openreview.net/forum?id=3bcN6xlO6f) (ICLR 2025), a new task that compares how an action is performed between two videos. This page introduces the task, the dataset structure, and how to access the data. See the paper for details on dataset construction. The code for running evaluation, and for benchmarking popular LMMs is at [https://jmhb0.github.io/viddiff](https://jmhb0.github.io/viddiff). ``` @inproceedings{burgessvideo, title={Video Action Differencing}, author={Burgess, James and Wang, Xiaohan and Zhang, Yuhui and Rau, Anita and Lozano, Alejandro and Dunlap, Lisa and Darrell, Trevor and Yeung-Levy, Serena}, booktitle={The Thirteenth International Conference on Learning Representations} } ``` # The Video Action Differencing task: closed and open evaluation The Video Action Differencing task compares two videos of the same action. The goal is to identify differences in how the action is performed, where the differences are expressed in natural language. ![morecontent](https://raw.githubusercontent.com/jmhb0/jmhb0.github.io/main/images/pull%20fig-5.jpg) In closed evaluation: - Input: two videos of the same action, action description string, a list of candidate difference strings. - Output: for each difference string, either 'a' if the statement applies more to video a, or 'b' if it applies more to video 'b'. In open evaluation, the model must generate the difference strings: - Input: two videos of the same action, action description string, a number 'n_differences'. - Output: a list of difference strings (at most 'n_differences'). For each difference string, 'a' if the statement applies more to video a, or 'b' if it applies more to video 'b'.  # Dataset structure After following the 'getting the data' section: we have `dataset` as a HuggingFace dataset and `videos` as a list. For row `i`: video A is `videos[0][i]`, video B is `videos[1][i]`, and `dataset[i]` is the annotation for the difference between the videos. The videos: - `videos[0][i]['video']` and is a numpy array with shape `(nframes,H,W,3)`. - `videos[0][i]['fps_original']` is an int, frames per second. The annotations in `dataset`: - `sample_key` a unique key. - `videos` metadata about the videos A and B used by the dataloader: the video filename, and the start and end frames. - `action` action key like "fitness_2" - `action_name` a short action name, like "deadlift" - `action_description` a longer action description, like "a single free weight deadlift without any weight" - `source_dataset` the source dataset for the videos (but not annotation), e.g. 'humman' [here](https://caizhongang.com/projects/HuMMan/). - `split` difficulty split, one of `{'easy', 'medium', 'hard'}` - `n_differences_open_prediction` in open evaluation, the max number of difference strings the model is allowed to generate. - `differences_annotated` a dict with the difference strings, e.g: ``` { "0": { "description": "the feet stance is wider", "name": "feet stance wider", "num_frames": "1", }, "1": { "description": "the speed of hip rotation is faster", "name": "speed", "num_frames": "gt_1", }, "2" : null, ... ``` - and these keys are: - the key is the 'key_difference' - `description` is the 'difference string' (passed as input in closed eval, or the model must generate a semantically similar string in open eval). - `num_frames` (not used) is '1' if an LMM could solve it from a single (well-chosen) frame, or 'gt_1' if more frames are needed. - Some values might be `null`. This is because the Huggingface datasets enforces that all elements in a column have the same schema. - `differences_gt` has the gt label, e.g. `{"0": "b", "1":"a", "2":null}`. For example, difference "the feet stance is wider" applies more to video B. - `domain` activity domain. One of `{'fitness', 'ballsports', 'diving', 'surgery', 'music'}`. # Getting the data Getting the dataset requires a few steps. We distribute the annotations, but since we don't own the videos, you'll have to download them elsewhere. **Get the annotations** First, get the annotations from the hub like this: ``` from datasets import load_dataset repo_name = "jmhb/VidDiffBench" dataset = load_dataset(repo_name) ``` **Get the videos** We get videos from prior works (which should be cited if you use the benchmark - see the end of this doc). The source dataset is in the dataset column `source_dataset`. First, download some `.py` files from this repo into your local `data/` file. ``` GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/jmhb/VidDiffBench data/ ``` A few datasets let us redistribute videos, so you can download them from this HF repo like this: ``` python data/download_data.py ``` If you ONLY need the 'easy' split, you can stop here. The videos includes the source datasets [Humann](https://caizhongang.com/projects/HuMMan/) (and 'easy' only draws from this data) and [JIGSAWS](https://cirl.lcsr.jhu.edu/research/hmm/datasets/jigsaws_release/). For 'medium' and 'hard' splits, you'll need to download these other datasets from the EgoExo4D and FineDiving. Here's how to do that: *Download EgoExo4d videos* These are needed for 'medium' and 'hard' splits. First Request an access key from the [docs](https://docs.ego-exo4d-data.org/getting-started/) (it takes 48hrs). Then follow the instructions to install the CLI download tool `egoexo`. We only need a small number of these videos, so get the uids list from `data/egoexo4d_uids.json` and use `egoexo` to download: ``` uids=$(jq -r '.[]' data/egoexo4d_uids.json | tr '\n' ' ' | sed 's/ $//') egoexo -o data/src_EgoExo4D --parts downscaled_takes/448 --uids $uids ``` Common issue: remember to put your access key into `~/.aws/credentials`. *Download FineDiving videos* These are needed for 'medium' split. Follow the instructions in [the repo](https://github.com/xujinglin/FineDiving) to request access (it takes at least a day), download the whole thing, and set up a link to it: ``` ln -s <path_to_fitnediving> data/src_FineDiving ``` **Making the final dataset with videos** Install these packages: ``` pip install numpy Pillow datasets decord lmdb tqdm huggingface_hub ``` Now run: ``` from data.load_dataset import load_dataset, load_all_videos dataset = load_dataset(splits=['easy'], subset_mode="0") # splits are one of {'easy','medium','hard'} videos = load_all_videos(dataset, cache=True, cache_dir="cache/cache_data") ``` For row `i`: video A is `videos[0][i]`, video B is `videos[1][i]`, and `dataset[i]` is the annotation for the difference between the videos. For video A, the video itself is `videos[0][i]['video']` and is a numpy array with shape `(nframes,3,H,W)`; the fps is in `videos[0][i]['fps_original']`. By passing the argument `cache=True` to `load_all_videos`, we create a cache directory at `cache/cache_data/`, and save copies of the videos using numpy memmap (total directory size for the whole dataset is 55Gb). Loading the videos and caching will take a few minutes per split (faster for the 'easy' split), and about 25mins for the whole dataset. But on subsequent runs, it should be fast - a few seconds for the whole dataset. Finally, you can get just subsets, for example setting `subset_mode='3_per_action'` will take 3 video pairs per action, while `subset_mode="0"` gets them all. # More dataset info We have more dataset metadata in this dataset repo: - Differences taxonomy `data/difference_taxonomy.csv`. - Actions and descriptions `data/actions.csv`. # License The annotations and all other non-video metadata is realeased under an MIT license. The videos retain the license of the original dataset creators, and the source dataset is given in dataset column `source_dataset`. - EgoExo4D, license is online at [this link](https://ego4d-data.org/pdfs/Ego-Exo4D-Model-License.pdf) - JIGSAWS release notes at [this link](https://cirl.lcsr.jhu.edu/research/hmm/datasets/jigsaws_release/ ) - Humman uses "S-Lab License 1.0" at [this link](https://caizhongang.com/projects/HuMMan/license.txt) - FineDiving use [this MIT license](https://github.com/xujinglin/FineDiving/blob/main/LICENSE) # Citation Below is the citation for our paper, and the original source datasets: ``` @inproceedings{burgessvideo, title={Video Action Differencing}, author={Burgess, James and Wang, Xiaohan and Zhang, Yuhui and Rau, Anita and Lozano, Alejandro and Dunlap, Lisa and Darrell, Trevor and Yeung-Levy, Serena}, booktitle={The Thirteenth International Conference on Learning Representations} } @inproceedings{cai2022humman, title={{HuMMan}: Multi-modal 4d human dataset for versatile sensing and modeling}, author={Cai, Zhongang and Ren, Daxuan and Zeng, Ailing and Lin, Zhengyu and Yu, Tao and Wang, Wenjia and Fan, Xiangyu and Gao, Yang and Yu, Yifan and Pan, Liang and Hong, Fangzhou and Zhang, Mingyuan and Loy, Chen Change and Yang, Lei and Liu, Ziwei}, booktitle={17th European Conference on Computer Vision, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part VII}, pages={557--577}, year={2022}, organization={Springer} } @inproceedings{parmar2022domain, title={Domain Knowledge-Informed Self-supervised Representations for Workout Form Assessment}, author={Parmar, Paritosh and Gharat, Amol and Rhodin, Helge}, booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XXXVIII}, pages={105--123}, year={2022}, organization={Springer} } @inproceedings{grauman2024ego, title={Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives}, author={Grauman, Kristen and Westbury, Andrew and Torresani, Lorenzo and Kitani, Kris and Malik, Jitendra and Afouras, Triantafyllos and Ashutosh, Kumar and Baiyya, Vijay and Bansal, Siddhant and Boote, Bikram and others}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={19383--19400}, year={2024} } @inproceedings{gao2014jhu, title={Jhu-isi gesture and skill assessment working set (jigsaws): A surgical activity dataset for human motion modeling}, author={Gao, Yixin and Vedula, S Swaroop and Reiley, Carol E and Ahmidi, Narges and Varadarajan, Balakrishnan and Lin, Henry C and Tao, Lingling and Zappella, Luca and B{\'e}jar, Benjam{\i}n and Yuh, David D and others}, booktitle={MICCAI workshop: M2cai}, volume={3}, number={2014}, pages={3}, year={2014} } ```

mshojaei77/PDC

mshojaei77

"2025-03-01T06:30:06Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:10:23Z"

--- dataset_info: features: - name: text dtype: string - name: file_name dtype: string splits: - name: train num_bytes: 1624495382 num_examples: 13111 download_size: 549673162 dataset_size: 1624495382 configs: - config_name: default data_files: - split: train path: data/train-* ---

simwit/medmoe-slake

simwit

"2025-03-01T07:53:30Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:27:40Z"

--- dataset_info: features: - name: image dtype: image - name: question dtype: string - name: answer dtype: string - name: modality dtype: string - name: answer_type dtype: string splits: - name: test_all num_bytes: 109097147.213 num_examples: 1061 - name: test_open num_bytes: 69131481.0 num_examples: 645 - name: test_closed num_bytes: 37653859.0 num_examples: 416 download_size: 27747526 dataset_size: 215882487.213 configs: - config_name: default data_files: - split: test_all path: data/test_all-* - split: test_open path: data/test_open-* - split: test_closed path: data/test_closed-* ---

Hkang/summarize_sft-test_lm-EleutherAI_pythia-1b_seed-42_numex-250_20K-BON_alpha-0.7_temp-0.7_64

Hkang

"2025-03-01T06:29:50Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:29:49Z"

--- dataset_info: features: - name: id dtype: string - name: subreddit dtype: string - name: title dtype: string - name: post dtype: string - name: summary dtype: string - name: query_input_ids sequence: int64 - name: query_attention_mask sequence: int64 - name: query dtype: string - name: reference_response dtype: string - name: reference_response_input_ids sequence: int64 - name: reference_response_attention_mask sequence: int64 - name: reference_response_token_len dtype: int64 - name: query_reference_response dtype: string - name: query_reference_response_input_ids sequence: int64 - name: query_reference_response_attention_mask sequence: int64 - name: query_reference_response_token_response_label sequence: int64 - name: query_reference_response_token_len dtype: int64 - name: model_response dtype: string splits: - name: test num_bytes: 6845542 num_examples: 250 download_size: 1156613 dataset_size: 6845542 configs: - config_name: default data_files: - split: test path: data/test-* ---

LunaCookie/RPG-datasets

LunaCookie

"2025-03-01T06:32:38Z"

0

[ "license:openrail", "size_categories:n<1K", "format:audiofolder", "modality:audio", "library:datasets", "library:mlcroissant", "region:us" ]

null

"2025-03-01T06:31:09Z"

--- license: openrail ---

simwit/medmoe-path-vqa

simwit

"2025-03-01T07:50:59Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:31:44Z"

--- dataset_info: features: - name: image dtype: image - name: question dtype: string - name: answer dtype: string - name: answer_type dtype: string splits: - name: test_all num_bytes: 487625910.222 num_examples: 6761 - name: test_open num_bytes: 428189626.97 num_examples: 3370 - name: test_closed num_bytes: 417624057.619 num_examples: 3391 download_size: 475692126 dataset_size: 1333439594.811 configs: - config_name: default data_files: - split: test_all path: data/test_all-* - split: test_open path: data/test_open-* - split: test_closed path: data/test_closed-* ---

isaiahbjork/showui-reasoning

isaiahbjork

"2025-03-01T06:32:30Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:32:01Z"

--- dataset_info: features: - name: conversation list: - name: content list: - name: text dtype: string - name: type dtype: string - name: role dtype: string - name: image dtype: binary splits: - name: train num_bytes: 9372012432 num_examples: 20000 download_size: 714885901 dataset_size: 9372012432 configs: - config_name: default data_files: - split: train path: data/train-* ---

Dhruveshsd/dvs

Dhruveshsd

"2025-03-01T06:33:45Z"

0

[ "license:bigscience-openrail-m", "region:us" ]

null

"2025-03-01T06:33:45Z"

--- license: bigscience-openrail-m ---

Yiheyihe/galaxea-r1-shelf-1ep-normalized

Yiheyihe

"2025-03-01T09:04:58Z"

0

[ "task_categories:robotics", "license:apache-2.0", "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "LeRobot" ]

[ "robotics" ]

"2025-03-01T06:42:10Z"

--- license: apache-2.0 task_categories: - robotics tags: - LeRobot configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": null, "total_episodes": 1, "total_frames": 508, "total_tasks": 1, "total_videos": 3, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "observation.state": { "dtype": "float32", "shape": [ 21 ] }, "action": { "dtype": "float32", "shape": [ 21 ] }, "observation.images.head": { "dtype": "video", "shape": [ 3, 94, 168 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 94, "video.width": 168, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.left_wrist": { "dtype": "video", "shape": [ 3, 94, 168 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 94, "video.width": 168, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.right_wrist": { "dtype": "video", "shape": [ 3, 94, 168 ], "names": [ "channels", "height", "width" ], "info": { "video.fps": 30.0, "video.height": 94, "video.width": 168, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

gajanhcc/fashion-detail-query-10images

gajanhcc

"2025-03-01T06:50:24Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:50:22Z"

--- dataset_info: features: - name: image dtype: image - name: item_ID dtype: string - name: query dtype: string - name: title dtype: string - name: position dtype: int64 - name: specific_detail_query dtype: string splits: - name: train num_bytes: 96642.7 num_examples: 7 - name: test num_bytes: 41418.3 num_examples: 3 download_size: 144469 dataset_size: 138061.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

jinchenliuljc/FinSumCOT

jinchenliuljc

"2025-03-01T06:58:05Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:51:50Z"

--- dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: text dtype: string - name: summary dtype: string - name: deepseek_summary dtype: string - name: deepseek_reasoning dtype: string splits: - name: train num_bytes: 86154 num_examples: 5 download_size: 66081 dataset_size: 86154 configs: - config_name: default data_files: - split: train path: data/train-* ---

gajanhcc/fashion-detail-query-annotated-10images

gajanhcc

"2025-03-01T07:06:29Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:52:49Z"

--- dataset_info: features: - name: image dtype: image - name: item_ID dtype: string - name: query dtype: string - name: title dtype: string - name: position dtype: int64 - name: original_image dtype: image - name: specific_detail_query dtype: string splits: - name: train num_bytes: 117483829.6 num_examples: 800 - name: test num_bytes: 29370957.4 num_examples: 200 download_size: 146828393 dataset_size: 146854787.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

svjack/Genshin_Impact_Yae_Miko_MMD_Video_Dataset

svjack

"2025-03-01T11:55:36Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:video", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T06:58:10Z"

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: video dtype: video splits: - name: train num_bytes: 1447150184.556 num_examples: 1061 download_size: 159078 dataset_size: 1447150184.556 --- <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/8aCjIslNTHwNqEENpgpg6.mp4"></video> Reorganized version of [`Wild-Heart/Disney-VideoGeneration-Dataset`](https://huggingface.co/datasets/Wild-Heart/Disney-VideoGeneration-Dataset). This is needed for [Mochi-1 fine-tuning](https://github.com/genmoai/mochi/tree/aba74c1b5e0755b1fa3343d9e4bd22e89de77ab1/demos/fine_tuner).

gymprathap/Driver-Distracted-Dataset

gymprathap

"2025-03-01T08:29:19Z"

0

[ "language:en", "license:cc", "size_categories:100K<n<1M", "modality:image", "region:us", "art" ]

null

"2025-03-01T07:04:54Z"

--- license: cc language: - en tags: - art size_categories: - 100K<n<1M ---

gajanhcc/fashion-detail-query-annotated-1000images

gajanhcc

"2025-03-01T07:09:51Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:09:43Z"

--- dataset_info: features: - name: image dtype: image - name: item_ID dtype: string - name: query dtype: string - name: title dtype: string - name: position dtype: int64 - name: original_image dtype: image - name: specific_detail_query dtype: string splits: - name: train num_bytes: 117483829.6 num_examples: 800 - name: test num_bytes: 29370957.4 num_examples: 200 download_size: 146828393 dataset_size: 146854787.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

khcho1954/ragas-test-dataset

khcho1954

"2025-03-01T07:11:43Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:09:50Z"

--- dataset_info: features: - name: contexts dtype: string - name: evolution_type dtype: string - name: metadata dtype: string - name: episode_done dtype: bool - name: question dtype: string - name: ground_truth dtype: string splits: - name: korean_v1 num_bytes: 30243 num_examples: 10 download_size: 0 dataset_size: 30243 configs: - config_name: default data_files: - split: korean_v1 path: data/korean_v1-* --- # Dataset Card for "ragas-test-dataset" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Arjuna17/lepala-ai-swahili-hausa-dataset

Arjuna17

"2025-03-01T07:11:27Z"

0

[ "license:apache-2.0", "region:us" ]

null

"2025-03-01T07:11:27Z"

--- license: apache-2.0 ---

Yuanxin-Liu/test_yx_noanswer-math_gsm-gemma-1.1-7b-it-iter_sample_7500_temp_1.0_gen_10_mlr5e-5

Yuanxin-Liu

"2025-03-01T07:19:22Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:19:20Z"

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: rational_answer dtype: string splits: - name: train num_bytes: 5409009 num_examples: 5802 download_size: 2877131 dataset_size: 5409009 configs: - config_name: default data_files: - split: train path: data/train-* ---

mangopy/ToolRet-before-sample

mangopy

"2025-03-01T07:39:53Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:25:37Z"

--- dataset_info: - config_name: apibank features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 189985 num_examples: 101 download_size: 45023 dataset_size: 189985 - config_name: apigen features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 991447 num_examples: 1000 download_size: 352171 dataset_size: 991447 - config_name: appbench features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2302790 num_examples: 801 download_size: 167561 dataset_size: 2302790 - config_name: autotools-food features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 783804 num_examples: 41 download_size: 138180 dataset_size: 783804 - config_name: autotools-music features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 8965195 num_examples: 50 download_size: 1884066 dataset_size: 8965195 - config_name: autotools-weather features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2171417 num_examples: 50 download_size: 369274 dataset_size: 2171417 - config_name: craft-math-algebra features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 328289 num_examples: 280 download_size: 119720 dataset_size: 328289 - config_name: craft-tabmwp features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 293350 num_examples: 174 download_size: 93220 dataset_size: 293350 - config_name: craft-vqa features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 270344 num_examples: 200 download_size: 85397 dataset_size: 270344 - config_name: gorilla-huggingface features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 831939 num_examples: 500 download_size: 290310 dataset_size: 831939 - config_name: gorilla-pytorch features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 295446 num_examples: 186 download_size: 43369 dataset_size: 295446 - config_name: gorilla-tensor features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 837843 num_examples: 688 download_size: 62197 dataset_size: 837843 - config_name: gpt4tools features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1607837 num_examples: 1727 download_size: 305122 dataset_size: 1607837 - config_name: gta features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 19979 num_examples: 14 download_size: 18173 dataset_size: 19979 - config_name: metatool features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2122091 num_examples: 5327 download_size: 516864 dataset_size: 2122091 - config_name: mnms features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 4932111 num_examples: 6874 download_size: 1411357 dataset_size: 4932111 - config_name: restgpt-spotify features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1764116 num_examples: 57 download_size: 292932 dataset_size: 1764116 - config_name: restgpt-tmdb features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 3540877 num_examples: 100 download_size: 1100630 dataset_size: 3540877 - config_name: reversechain features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 348064 num_examples: 200 download_size: 100619 dataset_size: 348064 - config_name: rotbench features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 488460 num_examples: 550 download_size: 92990 dataset_size: 488460 - config_name: t-eval-dialog features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 5585569 num_examples: 2660 download_size: 531217 dataset_size: 5585569 - config_name: t-eval-step features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1248324 num_examples: 553 download_size: 207806 dataset_size: 1248324 - config_name: taskbench-daily features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 5062303 num_examples: 4320 download_size: 838455 dataset_size: 5062303 - config_name: taskbench-huggingface features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 9117645 num_examples: 7546 download_size: 1489433 dataset_size: 9117645 - config_name: taskbench-multimedia features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 5191129 num_examples: 5584 download_size: 987374 dataset_size: 5191129 - config_name: tool-be-honest features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 466852 num_examples: 350 download_size: 166352 dataset_size: 466852 - config_name: toolace features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1498462 num_examples: 1000 download_size: 618326 dataset_size: 1498462 - config_name: toolalpaca features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 91909 num_examples: 94 download_size: 36261 dataset_size: 91909 - config_name: toolbench features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 2808494 num_examples: 1100 download_size: 922485 dataset_size: 2808494 - config_name: toolbench-sam features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 340762 num_examples: 387 download_size: 31793 dataset_size: 340762 - config_name: toolemu features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 1501848 num_examples: 144 download_size: 175104 dataset_size: 1501848 - config_name: tooleyes features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 335319 num_examples: 382 download_size: 58939 dataset_size: 335319 - config_name: toolink features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 562007 num_examples: 497 download_size: 114950 dataset_size: 562007 - config_name: toollens features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 45444525 num_examples: 18770 download_size: 1642020 dataset_size: 45444525 - config_name: ultratool features: - name: id dtype: string - name: query dtype: string - name: instruction dtype: string - name: labels dtype: string - name: category dtype: string splits: - name: queries num_bytes: 763581 num_examples: 500 download_size: 134582 dataset_size: 763581 configs: - config_name: apibank data_files: - split: queries path: apibank/queries-* - config_name: apigen data_files: - split: queries path: apigen/queries-* - config_name: appbench data_files: - split: queries path: appbench/queries-* - config_name: autotools-food data_files: - split: queries path: autotools-food/queries-* - config_name: autotools-music data_files: - split: queries path: autotools-music/queries-* - config_name: autotools-weather data_files: - split: queries path: autotools-weather/queries-* - config_name: craft-math-algebra data_files: - split: queries path: craft-math-algebra/queries-* - config_name: craft-tabmwp data_files: - split: queries path: craft-tabmwp/queries-* - config_name: craft-vqa data_files: - split: queries path: craft-vqa/queries-* - config_name: gorilla-huggingface data_files: - split: queries path: gorilla-huggingface/queries-* - config_name: gorilla-pytorch data_files: - split: queries path: gorilla-pytorch/queries-* - config_name: gorilla-tensor data_files: - split: queries path: gorilla-tensor/queries-* - config_name: gpt4tools data_files: - split: queries path: gpt4tools/queries-* - config_name: gta data_files: - split: queries path: gta/queries-* - config_name: metatool data_files: - split: queries path: metatool/queries-* - config_name: mnms data_files: - split: queries path: mnms/queries-* - config_name: restgpt-spotify data_files: - split: queries path: restgpt-spotify/queries-* - config_name: restgpt-tmdb data_files: - split: queries path: restgpt-tmdb/queries-* - config_name: reversechain data_files: - split: queries path: reversechain/queries-* - config_name: rotbench data_files: - split: queries path: rotbench/queries-* - config_name: t-eval-dialog data_files: - split: queries path: t-eval-dialog/queries-* - config_name: t-eval-step data_files: - split: queries path: t-eval-step/queries-* - config_name: taskbench-daily data_files: - split: queries path: taskbench-daily/queries-* - config_name: taskbench-huggingface data_files: - split: queries path: taskbench-huggingface/queries-* - config_name: taskbench-multimedia data_files: - split: queries path: taskbench-multimedia/queries-* - config_name: tool-be-honest data_files: - split: queries path: tool-be-honest/queries-* - config_name: toolace data_files: - split: queries path: toolace/queries-* - config_name: toolalpaca data_files: - split: queries path: toolalpaca/queries-* - config_name: toolbench data_files: - split: queries path: toolbench/queries-* - config_name: toolbench-sam data_files: - split: queries path: toolbench-sam/queries-* - config_name: toolemu data_files: - split: queries path: toolemu/queries-* - config_name: tooleyes data_files: - split: queries path: tooleyes/queries-* - config_name: toolink data_files: - split: queries path: toolink/queries-* - config_name: toollens data_files: - split: queries path: toollens/queries-* - config_name: ultratool data_files: - split: queries path: ultratool/queries-* --- 🔧 Retrieving useful tools from a large-scale toolset is an important step for Large language model (LLMs) in tool learning. This project (ToolRet) contribute to (i) _the first comprehensive tool retrieval benchmark_ to systematically evaluate existing information retrieval (IR) models on tool retrieval tasks; and (ii) a large-scale training dataset to optimize the expertise of IR models on this tool retrieval task. Our evaluation benchmark `ToolRet` is built by first collecting existing datasets and efficiently sample diverse retrieval tasks from them through K-means. This `ToolRet-before-sample` contains all raw datasets before K-means while the final version (after sampling) is released on [ToolRet](https://huggingface.co/datasets/mangopy/ToolRet-Tools).

akhooli/arabicweb24filtered

akhooli

"2025-03-01T08:21:23Z"

0

[ "size_categories:10M<n<100M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:27:43Z"

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 126409415256.64795 num_examples: 25394308 download_size: 60382553275 dataset_size: 126409415256.64795 configs: - config_name: default data_files: - split: train path: data/train-* ---

jinchenliuljc/FinSum

jinchenliuljc

"2025-03-01T09:43:36Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:48:35Z"

--- dataset_info: features: - name: text dtype: string - name: summary dtype: string - name: source dtype: string splits: - name: train num_bytes: 137444134 num_examples: 2305 - name: test num_bytes: 45668551 num_examples: 577 download_size: 88451041 dataset_size: 183112685 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

brunopbb/ufcg-labmet-fala-texto-main

brunopbb

"2025-03-01T07:49:37Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:49:20Z"

--- dataset_info: features: - name: id dtype: string - name: audio dtype: audio - name: transcription dtype: string splits: - name: train num_bytes: 98985053.0 num_examples: 507 - name: test num_bytes: 30899581.0 num_examples: 159 download_size: 126897890 dataset_size: 129884634.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

Yuanxin-Liu/test_yx_noanswer-math_gsm-gemma-2-9b-it-iter_sample_7500_temp_1.0_gen_10_mlr5e-5

Yuanxin-Liu

"2025-03-01T07:50:05Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:50:03Z"

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: rational_answer dtype: string splits: - name: train num_bytes: 6658223 num_examples: 6818 download_size: 3504453 dataset_size: 6658223 configs: - config_name: default data_files: - split: train path: data/train-* ---

keikhosrotav/tools-images

keikhosrotav

"2025-03-01T13:10:14Z"

0

[ "license:mit", "region:us" ]

null

"2025-03-01T07:53:17Z"

--- license: mit ---

fluff269/brainweb-ipp-train

fluff269

"2025-03-01T07:58:27Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:image", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:55:00Z"

--- dataset_info: features: - name: original_prompt dtype: string - name: original_image dtype: image - name: edit_prompt dtype: string - name: edited_prompt dtype: string - name: edited_image dtype: image splits: - name: train num_bytes: 1899382435.56 num_examples: 3620 download_size: 1898608370 dataset_size: 1899382435.56 configs: - config_name: default data_files: - split: train path: data/train-* ---

abhiakshat/testing_dataset

abhiakshat

"2025-03-01T07:58:29Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T07:58:25Z"

--- dataset_info: features: - name: file_name dtype: string - name: content dtype: string splits: - name: train num_bytes: 5183861 num_examples: 30 download_size: 1782569 dataset_size: 5183861 configs: - config_name: default data_files: - split: train path: data/train-* ---

FlippyDora/numia_prompt_reward_iter2_0-10000

FlippyDora

"2025-03-01T08:03:13Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:03:10Z"

--- dataset_info: features: - name: prompt dtype: string - name: responses sequence: string - name: gt dtype: string - name: problem dtype: string - name: rewards sequence: float64 splits: - name: train num_bytes: 215121274 num_examples: 10000 download_size: 82762031 dataset_size: 215121274 configs: - config_name: default data_files: - split: train path: data/train-* ---

Johnson111788/OpenImages_3DSR_feb27_unique_1k

Johnson111788

"2025-03-01T08:09:23Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:09:21Z"

--- dataset_info: features: - name: index dtype: string - name: question dtype: string - name: A dtype: string - name: B dtype: string - name: C dtype: string - name: D dtype: string - name: bounding_box list: - name: bbox_3d sequence: float64 - name: label dtype: string - name: direction list: - name: front_dir sequence: float64 - name: label dtype: string - name: left_dir sequence: float64 - name: answer dtype: string - name: answer_cot dtype: string - name: answer_name dtype: string - name: category dtype: string - name: image_url dtype: string splits: - name: train num_bytes: 1332953 num_examples: 792 - name: val num_bytes: 340836 num_examples: 204 download_size: 432413 dataset_size: 1673789 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* ---

lookas/astra_grab_floor_toys_base_cmd_pos

lookas

"2025-03-01T08:13:30Z"

0

[ "task_categories:robotics", "license:apache-2.0", "size_categories:10K<n<100K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us", "LeRobot", "astra" ]

[ "robotics" ]

"2025-03-01T08:11:28Z"

--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - astra configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": null, "total_episodes": 50, "total_frames": 73944, "total_tasks": 1, "total_videos": 150, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "action": { "dtype": "float32", "shape": [ 18 ], "names": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ] }, "observation.state": { "dtype": "float32", "shape": [ 18 ], "names": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 ] }, "action.arm_l": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "action.gripper_l": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "action.arm_r": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "action.gripper_r": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "action.base": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "action.eef_l": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "action.eef_r": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "action.head": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1 ] }, "observation.state.arm_l": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "observation.state.gripper_l": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "observation.state.arm_r": { "dtype": "float32", "shape": [ 6 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "observation.state.gripper_r": { "dtype": "float32", "shape": [ 1 ], "names": [ 0 ] }, "observation.state.base": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1, 2, 3, 4, 5 ] }, "observation.state.eef_l": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "observation.state.eef_r": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "observation.state.odom": { "dtype": "float32", "shape": [ 7 ], "names": [ 0, 1, 2, 3, 4, 5, 6 ] }, "observation.state.head": { "dtype": "float32", "shape": [ 2 ], "names": [ 0, 1 ] }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "observation.images.head": { "dtype": "video", "shape": [ 360, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 360, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.wrist_left": { "dtype": "video", "shape": [ 360, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 360, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.wrist_right": { "dtype": "video", "shape": [ 360, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 360, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

Yuanxin-Liu/test_yx_answer-math_gsm-gemma-2-9b-it-iter_sample_7500_temp_1.0_gen_10_mlr5e-5

Yuanxin-Liu

"2025-03-01T08:14:25Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:14:24Z"

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: rational_answer dtype: string splits: - name: train num_bytes: 6776189 num_examples: 6818 download_size: 3541819 dataset_size: 6776189 configs: - config_name: default data_files: - split: train path: data/train-* ---

SecondComming/style_transfer_testset

SecondComming

"2025-03-01T08:17:01Z"

0

[ "license:mit", "size_categories:n<1K", "format:imagefolder", "modality:image", "library:datasets", "library:mlcroissant", "region:us" ]

null

"2025-03-01T08:14:36Z"

--- license: mit ---

adalbertojunior/gsm8k-portuguese

adalbertojunior

"2025-03-01T08:14:51Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:14:47Z"

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string splits: - name: train num_bytes: 4334482 num_examples: 7473 - name: test num_bytes: 781310 num_examples: 1319 download_size: 2960234 dataset_size: 5115792 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

kngrg/wikifacts-sents-v2

kngrg

"2025-03-01T11:38:22Z"

0

[ "language:ru", "license:mit", "size_categories:1M<n<10M", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:19:46Z"

--- license: mit language: - ru configs: - config_name: corpus data_files: - corpus.jsonl - config_name: queries data_files: - queries.jsonl ---

kngrg/wikifacts-sents-v2-qrels

kngrg

"2025-03-01T10:27:44Z"

0

[ "language:ru", "license:mit", "size_categories:10K<n<100K", "format:csv", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:20:01Z"

--- license: mit language: - ru configs: - config_name: qrels data_files: - split: dev path: dev.tsv ---

friedrichor/DiDeMo

friedrichor

"2025-03-01T18:17:38Z"

0

[ "task_categories:text-to-video", "task_categories:text-retrieval", "task_categories:video-classification", "language:en", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

[ "text-to-video", "text-retrieval", "video-classification" ]

"2025-03-01T08:21:37Z"

--- configs: - config_name: default data_files: - split: train path: "didemo_train.json" - split: test path: "didemo_test.json" task_categories: - text-to-video - text-retrieval - video-classification language: - en size_categories: - 10K<n<100K --- [DiDeMo](https://openaccess.thecvf.com/content_iccv_2017/html/Hendricks_Localizing_Moments_in_ICCV_2017_paper.html) contains 10K long-form videos from Flickr. For each video, ~4 short sentences are annotated in temporal order. We follow the existing works to concatenate those short sentences and evaluate ‘paragraph-to-video’ retrieval on this benchmark. We adopt the official split: - Train: 8,395 videos, 8,395 captions (concatenate from 33,005 captions) - Val: 1,065 videos, 1,065 captions (concatenate from 4,290 captions) (We don't have the collection yet.) - Test: 1,004 videos, 1,004 captions (concatenate from 4,021 captions) --- Video Release: [DiDeMoRelease](https://data.ciirc.cvut.cz/public/projects/LisaAnne/DiDeMoRelease/)

sobiswriter/my-distiset-59f766b1

sobiswriter

"2025-03-01T08:33:28Z"

0

[ "task_categories:text-classification", "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "library:distilabel", "region:us", "synthetic", "distilabel", "rlaif", "datacraft" ]

[ "text-classification" ]

"2025-03-01T08:33:26Z"

--- size_categories: n<1K task_categories: - text-classification dataset_info: features: - name: text dtype: string - name: labels sequence: class_label: names: '0': average '1': low '2': efficient splits: - name: train num_bytes: 42680 num_examples: 85 download_size: 24094 dataset_size: 42680 configs: - config_name: default data_files: - split: train path: data/train-* tags: - synthetic - distilabel - rlaif - datacraft --- <p align="left"> <a href="https://github.com/argilla-io/distilabel"> <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/> </a> </p> # Dataset Card for my-distiset-59f766b1 This dataset has been created with [distilabel](https://distilabel.argilla.io/). ## Dataset Summary This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI: ```console distilabel pipeline run --config "https://huggingface.co/datasets/sobiswriter/my-distiset-59f766b1/raw/main/pipeline.yaml" ``` or explore the configuration: ```console distilabel pipeline info --config "https://huggingface.co/datasets/sobiswriter/my-distiset-59f766b1/raw/main/pipeline.yaml" ``` ## Dataset structure The examples have the following structure per configuration: <details><summary> Configuration: default </summary><hr> ```json { "labels": [ 0, 1, 2 ], "text": "Assuming a mid-size sedan vehicle with an estimated city cycle fuel economy of 35 miles per gallon, driven by a 45-year-old male with a moderate driving style under typical weather conditions with average temperatures between 65\u00b0F to 75\u00b0F\u0027, the classification of the vehicle\u0027s fuel efficiency must consider multiple variables, including the driver\u0027s idling behavior, starting habits, speed adherence, and driving route choice." } ``` This subset can be loaded as: ```python from datasets import load_dataset ds = load_dataset("sobiswriter/my-distiset-59f766b1", "default") ``` Or simply as it follows, since there's only one configuration and is named `default`: ```python from datasets import load_dataset ds = load_dataset("sobiswriter/my-distiset-59f766b1") ``` </details>

DariaaaS/characters_dataset1

DariaaaS

"2025-03-01T08:42:42Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:42:39Z"

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 32712.82608695652 num_examples: 83 - name: test num_bytes: 3547.1739130434785 num_examples: 9 download_size: 21797 dataset_size: 36260.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

infinite-dataset-hub/EventPhotographySnapshot

infinite-dataset-hub

"2025-03-01T08:43:34Z"

0

[ "license:mit", "size_categories:n<1K", "format:csv", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "infinite-dataset-hub", "synthetic" ]

null

"2025-03-01T08:43:33Z"

--- license: mit tags: - infinite-dataset-hub - synthetic --- # EventPhotographySnapshot tags: event, lighting, ML-task:Classification _Note: This is an AI-generated dataset so its content may be inaccurate or false_ **Dataset Description:** The 'EventPhotographySnapshot' dataset is a curated collection of textual descriptions of various event photography scenarios. Each entry provides a snapshot description and includes contextual details relevant to the lighting conditions, key subjects, and actions occurring within the image. This dataset aims to serve as a rich training ground for machine learning models focused on the classification of event photography based on composition, lighting, and other stylistic features. **CSV Content Preview:** ```csv "ID","Snippet","Label" "001","During the grand opening of the theater, a spotlight illuminates the stage, casting dramatic shadows.","Highlight" "002","A wedding reception's picturesque sunset, guests in festive attire against a backdrop of azure sky.","Wedding" "003","A dimly lit jazz club with a single spotlight shining on a saxophonist in mid-note.","Jazz Club" "004","A child's laughter echoes as they play with colorful balloons in a sunlit playground.","Children's Play" "005","Banquet hall during a banquet, the elegant table setting reflects the chandelier's soft glow.","Banquet" ``` The labels such as 'Highlight', 'Wedding', 'Jazz Club', 'Children's Play', and 'Banquet' are illustrative categories for classification tasks in event photography. The textual snippets provide context to machine learning models for understanding and classifying images based on their photographic content. **Source of the data:** The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'photography': - **Dataset Generation Page**: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=photography&dataset=EventPhotographySnapshot&tags=event,+lighting,+ML-task:Classification - **Model**: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct - **More Datasets**: https://huggingface.co/datasets?other=infinite-dataset-hub

Chand0320/fsd50k_test

Chand0320

"2025-03-01T08:50:46Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:50:44Z"

--- dataset_info: features: - name: audio sequence: int16 - name: sampling_rate dtype: int64 - name: id dtype: string - name: labels dtype: string splits: - name: train num_bytes: 22466493 num_examples: 20 download_size: 21078138 dataset_size: 22466493 configs: - config_name: default data_files: - split: train path: data/train-* ---

Tagiyevff/tradings

Tagiyevff

"2025-03-01T08:52:04Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:51:22Z"

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: response dtype: string splits: - name: train num_bytes: 39345.7476635514 num_examples: 149 - name: test num_bytes: 17164.252336448597 num_examples: 65 download_size: 14149 dataset_size: 56510.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

PhoenixZ/MM-AlignBench

PhoenixZ

"2025-03-01T09:21:14Z"

0

2

[ "arxiv:2502.18411", "region:us" ]

null

"2025-03-01T08:54:40Z"

--- dataset_info: features: - name: index dtype: string - name: question dtype: string - name: type dtype: string - name: claude3_sonnet dtype: string - name: image dtype: image - name: gt dtype: string splits: - name: test num_bytes: 26873033.0 num_examples: 252 download_size: 26095029 dataset_size: 26873033.0 --- ## Introduction Paper: [Paper](https://arxiv.org/abs/2502.18411), Github: [Github](https://github.com/PhoenixZ810/OmniAlign-V), Page: [Page](https://phoenixz810.github.io/OmniAlign-V/), SFT Dataset: [OmniAlign-V](https://huggingface.co/datasets/PhoenixZ/OmniAlign-V), DPO Dataset: [OmniAlign-V-DPO](https://huggingface.co/datasets/PhoenixZ/OmniAlign-V-DPO), **MM-AlignBench** is a benchmark designed to evaluate how well MLLMs align with human preferences. It consists of 252 high-quality, **human-annotated** samples , featuring diverse image types and open-ended questions. Inspired by Arena-style benchmarks, it employs: - GPT-4o as the judge model for scoring responses. - Claude-Sonnet-3 as the reference model for comparison. MM-AlignBench is now integrated into [VLMEvalkit](https://github.com/open-compass/VLMEvalKit), an open-source evaluation toolkit that supports over 200 MLLMs. You can quickly evaluate your model using the following steps: ``` git clone https://github.com/open-compass/VLMEvalKit.git cd VLMEvalKit pip install -e . python run.py --model MODEL_NAME --data MMAlignBench ``` For more details on **VLMEvalKit** , please refer to its [repository](https://github.com/open-compass/VLMEvalKit) ## LeaderBoard Below are the results of state-of-the-art MLLMs evaluated on **MM-AlignBench** : | Model | Win Rate | Reward | Better+ | Better | Tie | Worse | Worse+ | |-------------------------------|------------------------------|---------------------------|------------|-----|----|-----|-----| | Claude3.5V-Sonnet | 84.9 | +51.4 | 70 | 144 | 13 | 25 | 0 | | GPT-4o | 81.3 | +49.0 | 81 | 124 | 12 | 31 | 4 | | GPT-4V | 82.5 | +46.0 | 57 | 151 | 12 | 31 | 1 | | GeminiFlash1.5-002 | 77.0 | +39.1 | 56 | 138 | 14 | 35 | 9 | | LLaVANext-OA-32B-DPO | 74.2 | +36.9 | 49 | 138 | 20 | 40 | 5 | | Qwen2VL-72B | 61.5 | +21.6 | 43 | 112 | 15 | 75 | 7 | | LLaVANext-OA-32B | 62.3 | +19.4 | 31 | 126 | 19 | 62 | 14 | | Claude-3V-Sonnet | 50 | 0 | - | - | - | - | - | | Qwen2VL-7B | 44.4 | -5.8 | 28 | 84 | 5 | 101 | 34 | | InternVL2-72B | 44.4 | -6.9 | 19 | 93 | 8 | 98 | 34 | | InternVL2-8B-MPO | 40.1 | -10.9 | 26 | 75 | 10 | 100 | 41 | | InternVL2-8B | 31.3 | -21.8 | 18 | 61 | 15 | 109 | 49 | | LLaMA3.2-Vision-11B | 27.8 | -33.7 | 18 | 52 | 4 | 98 | 80 | | LLaVANext-Qwen32B | 26.6 | -29.0 | 16 | 51 | 10 | 121 | 54 | | LLaVA-OneVision-7B | 23.8 | -46.2 | 14 | 46 | 1 | 75 | 116 | | MiniCPM-V-2.5 | 12.7 | -53.0 | 9 | 23 | 8 | 116 | 96 | | Xcomposer2.5-7B | 7.5 | -74.0 | 5 | 14 | 3 | 63 | 167 | | Idefics3-8B | 2.7 | -92.3 | 3 | 4 | 0 | 15 | 230 |

dz237/finetuning_demo

dz237

"2025-03-01T08:54:58Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T08:54:56Z"

--- dataset_info: features: - name: prompt dtype: string splits: - name: train num_bytes: 107640 num_examples: 100 download_size: 33627 dataset_size: 107640 configs: - config_name: default data_files: - split: train path: data/train-* ---

svjack/Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned

svjack

"2025-03-01T12:09:17Z"

0

[ "size_categories:1K<n<10K", "modality:text", "modality:video", "library:datasets", "library:mlcroissant", "region:us" ]

null

"2025-03-01T08:58:38Z"

--- configs: - config_name: default data_files: - split: train path: - "*.mp4" - "metadata.csv" --- - In the style of Yae Miko , The video opens with a darkened scene where the details are not clearly visible. As the video progresses, the lighting improves, revealing a character dressed in traditional Japanese attire, standing on a stone pathway. The character is holding what appears to be a scroll or a piece of paper. Surrounding the character are several lanterns with intricate designs, casting a warm glow on the pathway and the character's clothing. In the background, there is a traditional Japanese building with red pillars and a tiled roof, partially obscured by cherry blossom trees in full bloom. The blossoms are pink and create a soft contrast against the night sky. The ground is covered with fallen petals, adding to the serene and picturesque setting. <video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/634dffc49b777beec3bc6448/tDDH_W8-iBY74bbay9WUX.mp4"></video> Reorganized version of [`Wild-Heart/Disney-VideoGeneration-Dataset`](https://huggingface.co/datasets/Wild-Heart/Disney-VideoGeneration-Dataset). This is needed for [Mochi-1 fine-tuning](https://github.com/genmoai/mochi/tree/aba74c1b5e0755b1fa3343d9e4bd22e89de77ab1/demos/fine_tuner). ```bash sudo apt-get update && sudo apt-get install cbm ffmpeg git-lfs pip install moviepy==1.0.3 opencv-python git clone https://huggingface.co/datasets/svjack/Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned git clone https://huggingface.co/datasets/svjack/genshin_impact_YAE_MIKO_images_and_styled_captions ``` ```python import os import cv2 import numpy as np from moviepy.editor import VideoFileClip from tqdm import tqdm import shutil def change_resolution_and_save(input_path, output_path, target_width=1024, target_height=768, max_duration=4): """处理图片和视频分辨率，添加黑边并分段处理视频""" os.makedirs(output_path, exist_ok=True) for root, dirs, files in os.walk(input_path): for file in tqdm(files, desc="Processing files"): file_path = os.path.join(root, file) relative_path = os.path.relpath(file_path, input_path) output_dir = os.path.dirname(os.path.join(output_path, relative_path)) # 处理图片 if file.lower().endswith(('.png', '.jpg', '.jpeg')): try: # 原图片处理逻辑 img = cv2.imread(file_path) h, w = img.shape[:2] scale = min(target_width / w, target_height / h) new_w = int(w * scale) new_h = int(h * scale) resized_img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA) background = np.zeros((target_height, target_width, 3), dtype=np.uint8) x_offset = (target_width - new_w) // 2 y_offset = (target_height - new_h) // 2 background[y_offset:y_offset+new_h, x_offset:x_offset+new_w] = resized_img output_file_path = os.path.join(output_path, relative_path) os.makedirs(os.path.dirname(output_file_path), exist_ok=True) cv2.imwrite(output_file_path, background) # 处理对应的txt文件 base_name = os.path.splitext(file)[0] txt_source = os.path.join(root, f"{base_name}.txt") if os.path.exists(txt_source): txt_target = os.path.join(output_dir, f"{base_name}.txt") shutil.copy2(txt_source, txt_target) except Exception as e: print(f"图片处理失败 {file_path}: {e}") # 处理视频 elif file.lower().endswith('.mp4'): try: clip = VideoFileClip(file_path) total_duration = clip.duration num_segments = int(total_duration // max_duration) # 处理每个分段 for i in range(num_segments): start_time = i * max_duration end_time = min((i+1) * max_duration, total_duration) sub_clip = clip.subclip(start_time, end_time) # 构造分段文件名 base_name = os.path.splitext(file)[0] output_filename = f"{base_name}_{i}.mp4" output_file_path = os.path.join(output_dir, output_filename) os.makedirs(os.path.dirname(output_file_path), exist_ok=True) # 处理视频帧 def process_frame(frame): img = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) h, w = img.shape[:2] scale = min(target_width / w, target_height / h) new_w = int(w * scale) new_h = int(h * scale) resized_img = cv2.resize(img, (new_w, new_h), interpolation=cv2.INTER_AREA) background = np.zeros((target_height, target_width, 3), dtype=np.uint8) x_offset = (target_width - new_w) // 2 y_offset = (target_height - new_h) // 2 background[y_offset:y_offset+new_h, x_offset:x_offset+new_w] = resized_img return cv2.cvtColor(background, cv2.COLOR_BGR2RGB) processed_clip = sub_clip.fl_image(process_frame) fps = processed_clip.fps if processed_clip.fps else 24 # 写入处理后的视频 processed_clip.write_videofile( output_file_path, codec='libx264', fps=fps, preset='slow', threads=4, audio=False ) processed_clip.close() # 处理对应的txt文件 txt_source = os.path.join(root, f"{base_name}.txt") if os.path.exists(txt_source): txt_target = os.path.join(output_dir, f"{base_name}_{i}.txt") shutil.copy2(txt_source, txt_target) clip.close() except Exception as e: print(f"视频处理失败 {file_path}: {e}") # 使用示例 change_resolution_and_save( input_path="Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned", output_path="Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned_512x384x1", target_width=512, target_height=384, max_duration=1 ) ''' change_resolution_and_save( input_path="genshin_impact_YAE_MIKO_images_and_styled_captions", output_path="genshin_impact_YAE_MIKO_images_and_styled_captions_1024x768x4", target_width=1024, target_height=768, max_duration=4 ) ''' ``` ```bash mkdir -p dataset/train cp Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned_512x384x1/*.mp4 dataset/train cp Genshin_Impact_Yae_Miko_MMD_Video_Dataset_Captioned_512x384x1/*.txt dataset/train cp genshin_impact_YAE_MIKO_images_and_styled_captions/*.png dataset/train cp genshin_impact_YAE_MIKO_images_and_styled_captions/*.txt dataset/train ```

DariaaaS/characters_dataset_no_tokens

DariaaaS

"2025-03-01T09:06:22Z"

0

[ "region:us" ]

null

"2025-03-01T09:06:19Z"

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 27898.82608695652 num_examples: 83 - name: test num_bytes: 3025.1739130434785 num_examples: 9 download_size: 20093 dataset_size: 30924.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

wangjl1512/so100_test

wangjl1512

"2025-03-01T11:00:44Z"

0

[ "task_categories:robotics", "license:apache-2.0", "size_categories:1K<n<10K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us", "LeRobot", "so100", "tutorial" ]

[ "robotics" ]

"2025-03-01T09:11:39Z"

--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - so100 - tutorial configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 1, "total_frames": 196, "total_tasks": 1, "total_videos": 1, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.images.laptop": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

Chand0320/fsd50k_test2

Chand0320

"2025-03-01T09:15:14Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:13:55Z"

--- dataset_info: features: - name: audio dtype: audio - name: id dtype: int64 - name: labels dtype: string splits: - name: train num_bytes: 22467864.0 num_examples: 20 download_size: 20743253 dataset_size: 22467864.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

NGMOB/distill_psychology-10k-r1.json

NGMOB

"2025-03-01T09:17:26Z"

0

[ "license:cc", "size_categories:1K<n<10K", "format:json", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:16:27Z"

--- license: cc ---

avrecum/r1_llama3_8b_activation_patched_outputs_2048

avrecum

"2025-03-01T09:18:09Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:18:06Z"

--- dataset_info: features: - name: question dtype: string - name: patched_output sequence: string - name: unpatched_output sequence: string splits: - name: train num_bytes: 552019 num_examples: 50 download_size: 223629 dataset_size: 552019 configs: - config_name: default data_files: - split: train path: data/train-* ---

tensorlink-dev/PTN-BTC-v2

tensorlink-dev

"2025-03-01T09:22:51Z"

0

[ "size_categories:100K<n<1M", "format:parquet", "modality:tabular", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:20:21Z"

--- dataset_info: features: - name: 'Unnamed: 0' dtype: int64 - name: volume dtype: float64 - name: vwap dtype: float64 - name: open dtype: float64 - name: close dtype: float64 - name: high dtype: float64 - name: low dtype: float64 - name: date dtype: timestamp[ns] - name: number_of_trades dtype: int64 - name: future_return dtype: float64 - name: atr dtype: float64 - name: rr-6 dtype: float64 - name: rr-12 dtype: float64 - name: rr-36 dtype: float64 - name: rr-144 dtype: float64 - name: rr-288 dtype: float64 - name: log_return dtype: float64 - name: simple_return dtype: float64 - name: cumulative_return dtype: float64 - name: volatility dtype: float64 - name: momentum dtype: float64 - name: zscore_price dtype: float64 - name: price_diff dtype: float64 - name: high_low_range dtype: float64 - name: open_close_range dtype: float64 - name: volume_change dtype: float64 - name: relative_volume dtype: float64 - name: volume_rolling_mean dtype: float64 - name: volume_rolling_std dtype: float64 - name: volume_zscore dtype: float64 - name: volume_surge dtype: float64 - name: price_range_vs_volume dtype: float64 - name: price_change dtype: float64 - name: price_volume_corr dtype: float64 - name: momentum_vs_volume dtype: float64 - name: log_return_vs_volume dtype: float64 - name: upper_wick dtype: float64 - name: lower_wick dtype: float64 - name: wick_ratio dtype: float64 - name: wick_vs_volume dtype: float64 - name: body_to_range_ratio dtype: float64 - name: open_close_ratio dtype: float64 - name: timestamp dtype: timestamp[ns] - name: hour dtype: int32 - name: minute dtype: int32 - name: hour_sin dtype: float64 - name: hour_cos dtype: float64 - name: minute_sin dtype: float64 - name: minute_cos dtype: float64 - name: hour_weighted_relative_volume dtype: float64 - name: minute_weighted_relative_volume dtype: float64 - name: hour_weighted_momentum dtype: float64 - name: minute_weighted_momentum dtype: float64 - name: hour_weighted_volatility dtype: float64 - name: minute_weighted_volatility dtype: float64 - name: hour_weighted_simple_return dtype: float64 - name: minute_weighted_simple_return dtype: float64 - name: hour_weighted_volume_zscore dtype: float64 - name: minute_weighted_volume_zscore dtype: float64 - name: hour_weighted_high_low_range dtype: float64 - name: minute_weighted_high_low_range dtype: float64 - name: hour_weighted_high dtype: float64 - name: minute_weighted_high dtype: float64 - name: hour_weighted_low dtype: float64 - name: minute_weighted_low dtype: float64 - name: hour_weighted_open dtype: float64 - name: minute_weighted_open dtype: float64 - name: hour_weighted_close dtype: float64 - name: minute_weighted_close dtype: float64 - name: hour_weighted_volume_change dtype: float64 - name: minute_weighted_volume_change dtype: float64 - name: hour_weighted_upper_wick dtype: float64 - name: minute_weighted_upper_wick dtype: float64 - name: hour_weighted_lower_wick dtype: float64 - name: minute_weighted_lower_wick dtype: float64 - name: hour_weighted_wick_ratio dtype: float64 - name: minute_weighted_wick_ratio dtype: float64 - name: hour_weighted_wick_vs_volume dtype: float64 - name: minute_weighted_wick_vs_volume dtype: float64 - name: hour_weighted_body_to_range_ratio dtype: float64 - name: minute_weighted_body_to_range_ratio dtype: float64 - name: hour_weighted_open_close_ratio dtype: float64 - name: minute_weighted_open_close_ratio dtype: float64 - name: log_return-12-mean dtype: float64 - name: log_return-12-diff dtype: float64 - name: log_return-36-mean dtype: float64 - name: log_return-36-diff dtype: float64 - name: log_return-144-mean dtype: float64 - name: log_return-144-diff dtype: float64 - name: log_return-288-mean dtype: float64 - name: log_return-288-diff dtype: float64 - name: log_return-864-mean dtype: float64 - name: log_return-864-diff dtype: float64 - name: simple_return-12-mean dtype: float64 - name: simple_return-12-diff dtype: float64 - name: simple_return-36-mean dtype: float64 - name: simple_return-36-diff dtype: float64 - name: simple_return-144-mean dtype: float64 - name: simple_return-144-diff dtype: float64 - name: simple_return-288-mean dtype: float64 - name: simple_return-288-diff dtype: float64 - name: simple_return-864-mean dtype: float64 - name: simple_return-864-diff dtype: float64 - name: cumulative_return-12-mean dtype: float64 - name: cumulative_return-12-diff dtype: float64 - name: cumulative_return-36-mean dtype: float64 - name: cumulative_return-36-diff dtype: float64 - name: cumulative_return-144-mean dtype: float64 - name: cumulative_return-144-diff dtype: float64 - name: cumulative_return-288-mean dtype: float64 - name: cumulative_return-288-diff dtype: float64 - name: cumulative_return-864-mean dtype: float64 - name: cumulative_return-864-diff dtype: float64 - name: volatility-12-mean dtype: float64 - name: volatility-12-diff dtype: float64 - name: volatility-36-mean dtype: float64 - name: volatility-36-diff dtype: float64 - name: volatility-144-mean dtype: float64 - name: volatility-144-diff dtype: float64 - name: volatility-288-mean dtype: float64 - name: volatility-288-diff dtype: float64 - name: volatility-864-mean dtype: float64 - name: volatility-864-diff dtype: float64 - name: momentum-12-mean dtype: float64 - name: momentum-12-diff dtype: float64 - name: momentum-36-mean dtype: float64 - name: momentum-36-diff dtype: float64 - name: momentum-144-mean dtype: float64 - name: momentum-144-diff dtype: float64 - name: momentum-288-mean dtype: float64 - name: momentum-288-diff dtype: float64 - name: momentum-864-mean dtype: float64 - name: momentum-864-diff dtype: float64 - name: zscore_price-12-mean dtype: float64 - name: zscore_price-12-diff dtype: float64 - name: zscore_price-36-mean dtype: float64 - name: zscore_price-36-diff dtype: float64 - name: zscore_price-144-mean dtype: float64 - name: zscore_price-144-diff dtype: float64 - name: zscore_price-288-mean dtype: float64 - name: zscore_price-288-diff dtype: float64 - name: zscore_price-864-mean dtype: float64 - name: zscore_price-864-diff dtype: float64 - name: price_diff-12-mean dtype: float64 - name: price_diff-12-diff dtype: float64 - name: price_diff-36-mean dtype: float64 - name: price_diff-36-diff dtype: float64 - name: price_diff-144-mean dtype: float64 - name: price_diff-144-diff dtype: float64 - name: price_diff-288-mean dtype: float64 - name: price_diff-288-diff dtype: float64 - name: price_diff-864-mean dtype: float64 - name: price_diff-864-diff dtype: float64 - name: high_low_range-12-mean dtype: float64 - name: high_low_range-12-diff dtype: float64 - name: high_low_range-36-mean dtype: float64 - name: high_low_range-36-diff dtype: float64 - name: high_low_range-144-mean dtype: float64 - name: high_low_range-144-diff dtype: float64 - name: high_low_range-288-mean dtype: float64 - name: high_low_range-288-diff dtype: float64 - name: high_low_range-864-mean dtype: float64 - name: high_low_range-864-diff dtype: float64 - name: open_close_range-12-mean dtype: float64 - name: open_close_range-12-diff dtype: float64 - name: open_close_range-36-mean dtype: float64 - name: open_close_range-36-diff dtype: float64 - name: open_close_range-144-mean dtype: float64 - name: open_close_range-144-diff dtype: float64 - name: open_close_range-288-mean dtype: float64 - name: open_close_range-288-diff dtype: float64 - name: open_close_range-864-mean dtype: float64 - name: open_close_range-864-diff dtype: float64 - name: volume_change-12-mean dtype: float64 - name: volume_change-12-diff dtype: float64 - name: volume_change-36-mean dtype: float64 - name: volume_change-36-diff dtype: float64 - name: volume_change-144-mean dtype: float64 - name: volume_change-144-diff dtype: float64 - name: volume_change-288-mean dtype: float64 - name: volume_change-288-diff dtype: float64 - name: volume_change-864-mean dtype: float64 - name: volume_change-864-diff dtype: float64 - name: relative_volume-12-mean dtype: float64 - name: relative_volume-12-diff dtype: float64 - name: relative_volume-36-mean dtype: float64 - name: relative_volume-36-diff dtype: float64 - name: relative_volume-144-mean dtype: float64 - name: relative_volume-144-diff dtype: float64 - name: relative_volume-288-mean dtype: float64 - name: relative_volume-288-diff dtype: float64 - name: relative_volume-864-mean dtype: float64 - name: relative_volume-864-diff dtype: float64 - name: volume_rolling_mean-12-mean dtype: float64 - name: volume_rolling_mean-12-diff dtype: float64 - name: volume_rolling_mean-36-mean dtype: float64 - name: volume_rolling_mean-36-diff dtype: float64 - name: volume_rolling_mean-144-mean dtype: float64 - name: volume_rolling_mean-144-diff dtype: float64 - name: volume_rolling_mean-288-mean dtype: float64 - name: volume_rolling_mean-288-diff dtype: float64 - name: volume_rolling_mean-864-mean dtype: float64 - name: volume_rolling_mean-864-diff dtype: float64 - name: volume_rolling_std-12-mean dtype: float64 - name: volume_rolling_std-12-diff dtype: float64 - name: volume_rolling_std-36-mean dtype: float64 - name: volume_rolling_std-36-diff dtype: float64 - name: volume_rolling_std-144-mean dtype: float64 - name: volume_rolling_std-144-diff dtype: float64 - name: volume_rolling_std-288-mean dtype: float64 - name: volume_rolling_std-288-diff dtype: float64 - name: volume_rolling_std-864-mean dtype: float64 - name: volume_rolling_std-864-diff dtype: float64 - name: volume_zscore-12-mean dtype: float64 - name: volume_zscore-12-diff dtype: float64 - name: volume_zscore-36-mean dtype: float64 - name: volume_zscore-36-diff dtype: float64 - name: volume_zscore-144-mean dtype: float64 - name: volume_zscore-144-diff dtype: float64 - name: volume_zscore-288-mean dtype: float64 - name: volume_zscore-288-diff dtype: float64 - name: volume_zscore-864-mean dtype: float64 - name: volume_zscore-864-diff dtype: float64 - name: volume_surge-12-mean dtype: float64 - name: volume_surge-12-diff dtype: float64 - name: volume_surge-36-mean dtype: float64 - name: volume_surge-36-diff dtype: float64 - name: volume_surge-144-mean dtype: float64 - name: volume_surge-144-diff dtype: float64 - name: volume_surge-288-mean dtype: float64 - name: volume_surge-288-diff dtype: float64 - name: volume_surge-864-mean dtype: float64 - name: volume_surge-864-diff dtype: float64 - name: price_range_vs_volume-12-mean dtype: float64 - name: price_range_vs_volume-12-diff dtype: float64 - name: price_range_vs_volume-36-mean dtype: float64 - name: price_range_vs_volume-36-diff dtype: float64 - name: price_range_vs_volume-144-mean dtype: float64 - name: price_range_vs_volume-144-diff dtype: float64 - name: price_range_vs_volume-288-mean dtype: float64 - name: price_range_vs_volume-288-diff dtype: float64 - name: price_range_vs_volume-864-mean dtype: float64 - name: price_range_vs_volume-864-diff dtype: float64 - name: price_change-12-mean dtype: float64 - name: price_change-12-diff dtype: float64 - name: price_change-36-mean dtype: float64 - name: price_change-36-diff dtype: float64 - name: price_change-144-mean dtype: float64 - name: price_change-144-diff dtype: float64 - name: price_change-288-mean dtype: float64 - name: price_change-288-diff dtype: float64 - name: price_change-864-mean dtype: float64 - 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name: hour_weighted_open_close_ratio-864-mean dtype: float64 - name: hour_weighted_open_close_ratio-864-diff dtype: float64 - name: minute_weighted_open_close_ratio-12-mean dtype: float64 - name: minute_weighted_open_close_ratio-12-diff dtype: float64 - name: minute_weighted_open_close_ratio-36-mean dtype: float64 - name: minute_weighted_open_close_ratio-36-diff dtype: float64 - name: minute_weighted_open_close_ratio-144-mean dtype: float64 - name: minute_weighted_open_close_ratio-144-diff dtype: float64 - name: minute_weighted_open_close_ratio-288-mean dtype: float64 - name: minute_weighted_open_close_ratio-288-diff dtype: float64 - name: minute_weighted_open_close_ratio-864-mean dtype: float64 - name: minute_weighted_open_close_ratio-864-diff dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1783200000 num_examples: 300000 - name: test num_bytes: 761283744 num_examples: 128076 download_size: 2762518533 dataset_size: 2544483744 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

hgissbkh/ner

hgissbkh

"2025-03-01T09:22:54Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:22:36Z"

--- dataset_info: features: - name: words sequence: string - name: ner sequence: class_label: names: '0': O '1': B-PER '2': I-PER '3': B-ORG '4': I-ORG '5': B-LOC '6': I-LOC '7': B-MISC '8': I-MISC - name: lang dtype: string splits: - name: train num_bytes: 3530082 num_examples: 14042 - name: validation num_bytes: 3397847 num_examples: 10944 - name: test num_bytes: 3848249 num_examples: 13186 download_size: 2573896 dataset_size: 10776178 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

hgissbkh/pos

hgissbkh

"2025-03-01T09:23:16Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:23:03Z"

--- dataset_info: features: - name: words sequence: string - name: pos sequence: class_label: names: '0': ADJ '1': ADP '2': ADV '3': AUX '4': CCONJ '5': DET '6': INTJ '7': NOUN '8': NUM '9': PART '10': PRON '11': PROPN '12': PUNCT '13': SCONJ '14': SYM '15': VERB '16': X - name: lang dtype: string splits: - name: train num_bytes: 7431679 num_examples: 25376 - name: validation num_bytes: 1488674 num_examples: 4915 - name: test num_bytes: 1130096 num_examples: 4072 download_size: 2275692 dataset_size: 10050449 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* ---

HKUSTAudio/VidMuse-V2M-Dataset

HKUSTAudio

"2025-03-01T09:39:03Z"

0

[ "license:cc-by-nc-4.0", "size_categories:100K<n<1M", "format:text", "modality:text", "library:datasets", "library:mlcroissant", "arxiv:2406.04321", "region:us" ]

null

"2025-03-01T09:24:00Z"

--- license: cc-by-nc-4.0 --- # V2M Dataset: A Large-Scale Video-to-Music Dataset 🎶 **The V2M dataset is proposed in the [VidMuse project](https://vidmuse.github.io/), aimed at advancing research in video-to-music generation.** ## ✨ Dataset Overview The V2M dataset comprises 360K pairs of videos and music, covering various types including movie trailers, advertisements, and documentaries. This dataset provides researchers with a rich resource to explore the relationship between video content and music generation. ## 🛠️ Usage Instructions - Download the dataset: ```bash git clone https://huggingface.co/datasets/HKUSTAudio/VidMuse-V2M-Dataset ``` - Dataset structure: ``` V2M/ ├── V2M.txt ├── V2M-20k.txt └── V2M-bench.txt ``` ## 🎯 Citation If you use the V2M dataset in your research, please consider citing: ``` @article{tian2024vidmuse, title={Vidmuse: A simple video-to-music generation framework with long-short-term modeling}, author={Tian, Zeyue and Liu, Zhaoyang and Yuan, Ruibin and Pan, Jiahao and Liu, Qifeng and Tan, Xu and Chen, Qifeng and Xue, Wei and Guo, Yike}, journal={arXiv preprint arXiv:2406.04321}, year={2024} } ```

LauKramer/learn_hf_food_not_food_image_captions

LauKramer

"2025-03-01T09:25:07Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:25:06Z"

--- dataset_info: features: - name: text dtype: string - name: label dtype: string splits: - name: train num_bytes: 20253 num_examples: 250 download_size: 11617 dataset_size: 20253 configs: - config_name: default data_files: - split: train path: data/train-* ---

notewee/drivethruthailand-labeled

notewee

"2025-03-01T11:59:15Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:image", "modality:tabular", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:25:24Z"

--- configs: - config_name: default data_files: - split: train path: data/train-* dataset_info: features: - name: file_name dtype: string - name: image dtype: binary - name: video_id dtype: string - name: frame_number dtype: int64 - name: timestamp dtype: float64 - name: road_type dtype: string - name: weather dtype: string - name: scene dtype: string - name: has_car dtype: int64 - name: has_motorcycle dtype: int64 - name: has_truck dtype: int64 - name: has_bus dtype: int64 - name: has_pedestrian dtype: int64 - name: has_bicycle dtype: int64 - name: has_traffic_light dtype: int64 - name: has_traffic_sign dtype: int64 splits: - name: train num_bytes: 129850347 num_examples: 107 download_size: 129818832 dataset_size: 129850347 --- # DriveThruThailand Labeled Dataset ## Dataset Description A collection of 107 screenshots from DriveThruThailand videos with labels. ### Features Each image includes the following features: - **file_name**: File name - **image_path**: Path to the image within the dataset - **video_id**: Source video ID - **frame_number**: Frame number in the source video - **timestamp**: Timestamp in seconds - **road_type**: Road type classification (highway, urban) - **weather**: Weather condition (clear, cloudy) - **scene**: Scene type (city, countryside) ### File Structure - `/images/`: Contains all the images - `metadata.csv`: Contains metadata for all images ### Usage This dataset can be used with Hugging Face's `datasets` library: ```python from datasets import load_dataset # Load the dataset dataset = load_dataset("notewee/drivethruthailand-labeled") # Access metadata metadata = pd.read_csv(dataset["metadata.csv"]) # Access images image_paths = metadata["image_path"].tolist() ``` ## License CC-BY-4.0

haesleinhuepf/SlightInsight_Cache

haesleinhuepf

"2025-03-01T13:00:42Z"

0

[ "size_categories:1K<n<10K", "format:parquet", "modality:text", "modality:timeseries", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:34:01Z"

--- dataset_info: features: - name: key dtype: string - name: zenodo_record_id dtype: string - name: zenodo_filename dtype: string - name: page_number dtype: int64 - name: text sequence: float32 - name: visual sequence: float64 - name: mixed sequence: float32 splits: - name: train num_bytes: 32425773 num_examples: 2617 download_size: 34100658 dataset_size: 32425773 configs: - config_name: default data_files: - split: train path: data/train-* ---

DariaaaS/characters_csv

DariaaaS

"2025-03-01T09:35:54Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:34:31Z"

--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: train num_bytes: 25512.695652173912 num_examples: 82 - name: test num_bytes: 3111.304347826087 num_examples: 10 download_size: 22263 dataset_size: 28624.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

Chan-Y/full-311k

Chan-Y

"2025-03-01T10:02:32Z"

0

[ "size_categories:100K<n<1M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:38:44Z"

--- dataset_info: features: - name: question dtype: string - name: thinking dtype: string - name: answer dtype: string splits: - name: train num_bytes: 2968707254 num_examples: 311713 download_size: 1348665307 dataset_size: 2968707254 configs: - config_name: default data_files: - split: train path: data/train-* ---

yadunund/so100_test

yadunund

"2025-03-01T09:39:14Z"

0

[ "task_categories:robotics", "license:apache-2.0", "size_categories:n<1K", "format:parquet", "modality:tabular", "modality:timeseries", "modality:video", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us", "LeRobot", "so100", "tutorial" ]

[ "robotics" ]

"2025-03-01T09:39:11Z"

--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - so100 - tutorial configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 1, "total_frames": 150, "total_tasks": 1, "total_videos": 1, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:1" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.images.camera": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

ayushayush591/cross_lingual

ayushayush591

"2025-03-01T09:45:11Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:45:09Z"

--- dataset_info: features: - name: input dtype: string - name: output dtype: string splits: - name: validation num_bytes: 71317.62 num_examples: 99 download_size: 50109 dataset_size: 71317.62 configs: - config_name: default data_files: - split: validation path: data/validation-* ---

Mohamed-DLM/asr_en_ar_switch_split_117_final_updated

Mohamed-DLM

"2025-03-01T09:58:57Z"

0

[ "size_categories:n<1K", "format:parquet", "modality:audio", "modality:text", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:47:55Z"

--- dataset_info: features: - name: audio dtype: audio: sampling_rate: 16000 - name: transcription dtype: string splits: - name: train num_bytes: 5410674.0 num_examples: 57 download_size: 4813550 dataset_size: 5410674.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

H1tak3/phishing-html-tokenized

H1tak3

"2025-03-01T09:59:48Z"

0

[ "size_categories:10K<n<100K", "format:parquet", "library:datasets", "library:pandas", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T09:59:44Z"

--- dataset_info: features: - name: input_ids sequence: int32 - name: attention_mask sequence: int8 - name: labels dtype: int64 splits: - name: train num_bytes: 26674480 num_examples: 10355 - name: validation num_bytes: 6671840 num_examples: 2590 download_size: 8349661 dataset_size: 33346320 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

g-ronimo/IN1k256-AR-buckets-latents_dc-ae-f32c32-sana-1.0

g-ronimo

"2025-03-01T15:22:18Z"

0

[ "size_categories:1M<n<10M", "format:parquet", "modality:text", "library:datasets", "library:dask", "library:mlcroissant", "library:polars", "region:us" ]

null

"2025-03-01T10:03:38Z"

--- dataset_info: features: - name: label dtype: string - name: latent sequence: sequence: sequence: sequence: float32 configs: - config_name: default data_files: - split: train path: data/train_* - split: validation path: data/validation_* - split: train_AR_4_to_3 path: data/train_AR_4_to_3.* - split: train_AR_3_to_4 path: data/train_AR_3_to_4.* - split: train_AR_1_to_1 path: data/train_AR_1_to_1.* - split: validation_AR_4_to_3 path: data/validation_AR_4_to_3.* - split: validation_AR_3_to_4 path: data/validation_AR_3_to_4.* - split: validation_AR_1_to_1 path: data/validation_AR_1_to_1.* ---