open-hdscan-april3
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/open-hdscan-april3")
topic_model.get_topic_info()
Topic overview
- Number of topics: 11
- Number of training documents: 2779
Click here for an overview of all topics.
Topic ID | Topic Keywords | Topic Frequency | Label |
---|---|---|---|
-1 | models - language - model - llms - language models | 11 | -1_models_language_model_llms |
0 | models - language - model - language models - llms | 792 | 0_models_language_model_language models |
1 | code - models - llms - language - language models | 1082 | 1_code_models_llms_language |
2 | models - quantization - model - training - language | 311 | 2_models_quantization_model_training |
3 | models - bias - text - language - biases | 297 | 3_models_bias_text_language |
4 | brain - models - language - heads - attention | 152 | 4_brain_models_language_heads |
5 | hallucinations - hallucination - models - visual - large | 34 | 5_hallucinations_hallucination_models_visual |
6 | music - audio - poetry - generation - model | 31 | 6_music_audio_poetry_generation |
7 | financial - analysis - sentiment - investment - large | 30 | 7_financial_analysis_sentiment_investment |
8 | editing - knowledge - model editing - editing methods - edit | 25 | 8_editing_knowledge_model editing_editing methods |
9 | materials - molecular - chemical - chemistry - materials science | 14 | 9_materials_molecular_chemical_chemistry |
Training hyperparameters
- calculate_probabilities: False
- language: english
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: 11
- 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: 0.5.6
- Pandas: 2.0.3
- 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
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