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BERTopic_Legal
karinegabsschon/BERTopic_Legal
BERTopic_Legal is a text classification model from karinegabsschon. 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
- Jul 7, 2025
- Updated
- Sep 1, 2025
- SHA
- c5efe709
Try a prompt
Model card
From the Hugging Face model README
BERTopic_Legal
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("karinegabsschon/BERTopic_Legal")
topic_model.get_topic_info()
Topic overview
- Number of topics: 9
- Number of training documents: 199
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | electric - vehicles - ev - electric vehicles - charging | 6 | -1_electric_vehicles_ev_electric vehicles |
| 0 | cars - vehicles - electric - car - parking | 58 | 0_cars_vehicles_electric_car |
| 1 | chinese - electric - byd - china - cars | 30 | 1_chinese_electric_byd_china |
| 2 | charging - charge - ev - public - electric | 27 | 2_charging_charge_ev_public |
| 3 | tesla - musk - dollars - elon - elon musk | 23 | 3_tesla_musk_dollars_elon |
| 4 | new - electric - vehicles - car - drivers | 21 | 4_new_electric_vehicles_car |
| 5 | porsche - taycan - car - electric - garage | 13 | 5_porsche_taycan_car_electric |
| 6 | foxconn - mitsubishi - japanese - nissan - electric | 11 | 6_foxconn_mitsubishi_japanese_nissan |
| 7 | nikola - bankruptcy - lucid - northvolt - assets | 10 | 7_nikola_bankruptcy_lucid_northvolt |
Training hyperparameters
- calculate_probabilities: False
- language: None
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: None
- seed_topic_list: None
- top_n_words: 10
- verbose: True
- zeroshot_min_similarity: 0.7
- zeroshot_topic_list: None
Framework versions
- Numpy: 2.0.2
- HDBSCAN: 0.8.40
- UMAP: 0.5.8
- Pandas: 2.2.2
- Scikit-Learn: 1.6.1
- Sentence-transformers: 4.1.0
- Transformers: 4.53.0
- Numba: 0.60.0
- Plotly: 5.24.1
- Python: 3.11.13
- Task
- Text Classification
- Library
- bertopic
- Created
- Jul 7, 2025
- Updated
- Sep 1, 2025