Add BERTopic model
Browse files- README.md +89 -0
- config.json +17 -0
- ctfidf.bin +3 -0
- ctfidf_config.json +0 -0
- topic_embeddings.bin +3 -0
- topics.json +4349 -0
README.md
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---
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tags:
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- bertopic
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library_name: bertopic
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pipeline_tag: text-classification
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---
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# china-only-mar11
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
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BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
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## Usage
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To use this model, please install BERTopic:
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```
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pip install -U bertopic
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```
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You can use the model as follows:
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```python
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from bertopic import BERTopic
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topic_model = BERTopic.load("Thang203/china-only-mar11")
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topic_model.get_topic_info()
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```
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## Topic overview
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* Number of topics: 20
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* Number of training documents: 847
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<details>
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<summary>Click here for an overview of all topics.</summary>
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| Topic ID | Topic Keywords | Topic Frequency | Label |
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|----------|----------------|-----------------|-------|
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| -1 | language - llms - models - data - large | 21 | -1_language_llms_models_data |
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| 0 | visual - image - multimodal - models - language | 205 | 0_visual_image_multimodal_models |
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| 1 | embodied - driving - navigation - robot - robotic | 142 | 1_embodied_driving_navigation_robot |
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| 2 | recommendation - user - recommendations - systems - behavior | 16 | 2_recommendation_user_recommendations_systems |
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| 3 | agents - social - bots - interactions - ai agents | 16 | 3_agents_social_bots_interactions |
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| 4 | rl - reinforcement learning - reinforcement - learning - policy | 15 | 4_rl_reinforcement learning_reinforcement_learning |
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| 5 | molecular - design - property - prediction - gnns | 17 | 5_molecular_design_property_prediction |
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| 6 | code - code generation - generation - software - programming | 11 | 6_code_code generation_generation_software |
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| 7 | medical - knowledge - medical knowledge - llms - language | 73 | 7_medical_knowledge_medical knowledge_llms |
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| 8 | extraction - information extraction - event - information - relation | 16 | 8_extraction_information extraction_event_information |
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| 9 | safety - llms - robustness - instructions - assurance | 15 | 9_safety_llms_robustness_instructions |
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| 10 | reasoning - prompting - cot - llms - chainofthought | 14 | 10_reasoning_prompting_cot_llms |
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| 11 | knowledge - language - knowledge graph - web - kg | 52 | 11_knowledge_language_knowledge graph_web |
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| 12 | question - answering - commonsense - question answering - knowledge | 17 | 12_question_answering_commonsense_question answering |
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| 13 | models - language - model - training - language models | 18 | 13_models_language_model_training |
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| 14 | dialogue - dialog - models - responses - model | 104 | 14_dialogue_dialog_models_responses |
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| 15 | detection - fake - news - detectors - texts | 31 | 15_detection_fake_news_detectors |
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| 16 | chatgpt - sentiment - evaluation - sentiment analysis - human | 16 | 16_chatgpt_sentiment_evaluation_sentiment analysis |
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| 17 | chinese - evaluation - models - language - language models | 22 | 17_chinese_evaluation_models_language |
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| 18 | translation - arabic - languages - language - models | 26 | 18_translation_arabic_languages_language |
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</details>
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## Training hyperparameters
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* calculate_probabilities: False
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* language: english
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* low_memory: False
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* min_topic_size: 10
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* n_gram_range: (1, 1)
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* nr_topics: 20
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* seed_topic_list: None
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* top_n_words: 10
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* verbose: True
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* zeroshot_min_similarity: 0.7
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* zeroshot_topic_list: None
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## Framework versions
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* Numpy: 1.25.2
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* HDBSCAN: 0.8.33
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* UMAP: 0.5.5
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* Pandas: 1.5.3
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* Scikit-Learn: 1.2.2
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* Sentence-transformers: 2.6.1
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* Transformers: 4.38.2
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* Numba: 0.58.1
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* Plotly: 5.15.0
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* Python: 3.10.12
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config.json
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{
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"calculate_probabilities": false,
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"language": "english",
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"low_memory": false,
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"min_topic_size": 10,
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"n_gram_range": [
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1,
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1
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],
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"nr_topics": 20,
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"seed_topic_list": null,
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"top_n_words": 10,
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"verbose": true,
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"zeroshot_min_similarity": 0.7,
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"zeroshot_topic_list": null,
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
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}
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ctfidf.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b3df8db0886f06f232971e6dad2a1e5c6fabe7e4fdaad4820821e1c05e3988e9
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size 642947
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ctfidf_config.json
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The diff for this file is too large to render.
See raw diff
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topic_embeddings.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:cc09b35b41a7d32f40899ea13408958658520e42a1659af2d3361e4fda518ad7
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size 32009
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topics.json
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