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--- |
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dataset_info: |
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features: |
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- name: messages |
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list: |
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- name: content |
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dtype: string |
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- name: role |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 902953 |
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num_examples: 2446 |
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download_size: 246445 |
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dataset_size: 902953 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- text-generation |
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- text2text-generation |
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- question-answering |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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|
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## Description |
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The dataset is from [medalpaca/medical_meadow_pubmed_causal](https://huggingface.co/datasets/medalpaca/medical_meadow_pubmed_causal), formatted as dialogues for speed and ease of use. Many thanks to author for releasing it. |
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Importantly, this format is easy to use via the default chat template of `transformers`, meaning you can use [huggingface/alignment-handbook](https://github.com/huggingface/alignment-handbook) immediately, [unsloth](https://github.com/unslothai/unsloth). |
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## Structure |
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*View online through viewer.* |
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## Note |
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We advise you to reconsider before use, thank you. If you find it useful, please like and follow this account. |
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## Reference |
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The **Ghost X** was developed with the goal of researching and developing artificial intelligence useful to humans. |
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|
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- HuggingFace: [ghost-x](https://huggingface.co/ghost-x) |
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- Github: [ghost-x-ai](https://github.com/ghost-x-ai) |
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- X / Twitter: [ghostx_ai](https://twitter.com/ghostx_ai) |
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- Website: [ghost-x.org](https://ghost-x.org/) |
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## Citation |
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|
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```json |
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@inproceedings{yu-etal-2019-detecting, |
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title = "Detecting Causal Language Use in Science Findings", |
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author = "Yu, Bei and |
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Li, Yingya and |
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Wang, Jun", |
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booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)", |
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month = nov, |
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year = "2019", |
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address = "Hong Kong, China", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/D19-1473", |
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doi = "10.18653/v1/D19-1473", |
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pages = "4664--4674", |
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} |
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``` |
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### ~ |
