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jaria_topics
caiocof/jaria_topics
jaria_topics is a text classification model from caiocof. 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.
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At a glance
- Task
- Text Classification
- Library
- bertopic
- Access
- Public
- Created
- Apr 2, 2025
- Updated
- Apr 2, 2025
- SHA
- 44939d0f
Try a prompt
Model card
From the Hugging Face model README
jaria_topics
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("caiocof/jaria_topics")
topic_model.get_topic_info()
Topic overview
- Number of topics: 2
- Number of training documents: 206
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| 0 | de - do - da - no - que | 182 | 0_de_do_da_no |
| 1 | legalidade - do - ait - da - princípio | 24 | 1_legalidade_do_ait_da |
Training hyperparameters
- calculate_probabilities: False
- language: portuguese
- 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: 1.26.4
- HDBSCAN: 0.8.40
- UMAP: 0.5.7
- Pandas: 1.5.3
- Scikit-Learn: 1.3.0
- Sentence-transformers: 4.0.1
- Transformers: 4.48.1
- Numba: 0.59.1
- Plotly: 5.22.0
- Python: 3.12.4
- Task
- Text Classification
- Library
- bertopic
- Created
- Apr 2, 2025
- Updated
- Apr 2, 2025