Add BERTopic model
Browse files- README.md +81 -0
- config.json +17 -0
- ctfidf.bin +3 -0
- ctfidf_config.json +0 -0
- topic_embeddings.bin +3 -0
- topics.json +2626 -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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# industry-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/industry-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: 12
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* Number of training documents: 516
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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 | models - language - data - large - language models | 51 | -1_models_language_data_large |
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| 0 | multimodal - visual - image - models - generation | 169 | 0_multimodal_visual_image_models |
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| 1 | speech - asr - text - speaker - recognition | 24 | 1_speech_asr_text_speaker |
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| 2 | detection - models - text - language - model | 21 | 2_detection_models_text_language |
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| 3 | code - language - llms - models - programming | 32 | 3_code_language_llms_models |
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| 4 | agents - policy - language - learning - tasks | 49 | 4_agents_policy_language_learning |
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| 5 | reasoning - cot - problems - models - commonsense | 22 | 5_reasoning_cot_problems_models |
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| 6 | retrieval - information - query - llms - queries | 19 | 6_retrieval_information_query_llms |
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| 7 | ai - models - language - dialogue - human | 15 | 7_ai_models_language_dialogue |
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| 8 | language - models - translation - model - language models | 47 | 8_language_models_translation_model |
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| 9 | distillation - model - knowledge - pretrained - student | 51 | 9_distillation_model_knowledge_pretrained |
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| 10 | training - model - models - transformer - language | 16 | 10_training_model_models_transformer |
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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 sha256:22ea0d7033415f0d68f6e5b3563bed34d3c00987d2b635e6211ee2d6cd012bc3
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size 343171
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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 sha256:29deb3b6f42441c41506dbeced18ce744b1a821a350aadaa3e1af29304b1edc6
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size 19721
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topics.json
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