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close-mar11
Thang203/close-mar11
close-mar11 is a text classification model from Thang203. Use it when you need a label for a piece of text. It is set up for bertopic.
This is a BERTopic model. BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
All-time downloads
103
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Repo size
2.9 MB
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At a glance
- Task
- Text Classification
- Library
- bertopic
- Access
- Public
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024
- SHA
- 847bd103
Try a prompt
Model card
From the Hugging Face model README
close-mar11
This is a BERTopic model. BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
Usage
To use this model, please install BERTopic:
pip install -U bertopic
You can use the model as follows:
from bertopic import BERTopic
topic_model = BERTopic.load("Thang203/close-mar11")
topic_model.get_topic_info()
Topic overview
- Number of topics: 20
- Number of training documents: 4147
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | models - language - llms - language models - chatgpt | 11 | -1_models_language_llms_language models |
| 0 | code - models - language - llms - language models | 1366 | 0_code_models_language_llms |
| 1 | medical - clinical - models - llms - language | 840 | 1_medical_clinical_models_llms |
| 2 | language - models - human - model - llms | 310 | 2_language_models_human_model |
| 3 | bias - llms - language - models - biases | 196 | 3_bias_llms_language_models |
| 4 | attacks - adversarial - attack - llms - security | 188 | 4_attacks_adversarial_attack_llms |
| 5 | visual - image - multimodal - models - video | 184 | 5_visual_image_multimodal_models |
| 6 | text - detection - chatgpt - models - content | 175 | 6_text_detection_chatgpt_models |
| 7 | reasoning - language - models - mathematical - logical | 173 | 7_reasoning_language_models_mathematical |
| 8 | students - chatgpt - education - learning - programming | 119 | 8_students_chatgpt_education_learning |
| 9 | training - models - model - transformer - transformers | 109 | 9_training_models_model_transformer |
| 10 | ai - chatgpt - ethical - concerns - research | 106 | 10_ai_chatgpt_ethical_concerns |
| 11 | ai - design - creative - generative - ideas | 84 | 11_ai_design_creative_generative |
| 12 | financial - sentiment - stock - market - investment | 68 | 12_financial_sentiment_stock_market |
| 13 | spatial - urban - models - traffic - large | 52 | 13_spatial_urban_models_traffic |
| 14 | materials - chemistry - drug - discovery - molecule | 41 | 14_materials_chemistry_drug_discovery |
| 15 | legal - analysis - law - llms - lawyers | 35 | 15_legal_analysis_law_llms |
| 16 | recommendation - recommender - recommender systems - systems - recommendations | 35 | 16_recommendation_recommender_recommender systems_systems |
| 17 | game - agents - games - llms - playing | 30 | 17_game_agents_games_llms |
| 18 | astronomy - scientific - knowledge - galactica - data | 25 | 18_astronomy_scientific_knowledge_galactica |
Training hyperparameters
- calculate_probabilities: False
- language: None
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: 20
- seed_topic_list: None
- top_n_words: 10
- verbose: True
- zeroshot_min_similarity: 0.7
- zeroshot_topic_list: None
Framework versions
- Numpy: 1.25.2
- HDBSCAN: 0.8.33
- UMAP: 0.5.5
- Pandas: 1.5.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.6.1
- Transformers: 4.38.2
- Numba: 0.58.1
- Plotly: 5.15.0
- Python: 3.10.12
- Task
- Text Classification
- Library
- bertopic
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024