BERTopic_vafn
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("ychu612/BERTopic_vafn")
topic_model.get_topic_info()
Topic overview
- Number of topics: 3
- Number of training documents: 103
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | the - was - she - and - to | 15 | -1_the_was_she_and |
| 0 | the - she - was - and - her | 55 | 0_the_she_was_and |
| 1 | the - was - he - and - to | 33 | 1_the_was_he_and |
Training hyperparameters
- calculate_probabilities: False
- language: english
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: None
- seed_topic_list: None
- top_n_words: 10
- verbose: False
- zeroshot_min_similarity: 0.7
- zeroshot_topic_list: None
Framework versions
- Numpy: 1.23.0
- HDBSCAN: 0.8.33
- UMAP: 0.5.5
- Pandas: 2.1.4
- Scikit-Learn: 1.1.0
- Sentence-transformers: 2.3.1
- Transformers: 4.38.1
- Numba: 0.56.4
- Plotly: 5.9.0
- Python: 3.10.9
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