--- tags: - bertopic library_name: bertopic pipeline_tag: text-classification --- # BERTopic_generationidentitaire This is a [BERTopic](https://github.com/MaartenGr/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: ```python from bertopic import BERTopic topic_model = BERTopic.load("sdantonio/BERTopic_generationidentitaire") topic_model.get_topic_info() ``` ## Topic overview * Number of topics: 6 * Number of training documents: 1102
Click here for an overview of all topics. | Topic ID | Topic Keywords | Topic Frequency | Label | |----------|----------------|-----------------|-------| | -1 | france - lyonnaise - grenoble - peines - militants | 23 | -1_france_lyonnaise_grenoble_peines | | 0 | identitaires - france - lyonnais - montpellier - migrants | 12 | 0_identitaires_france_lyonnais_montpellier | | 1 | identitaires - france - turquie - imposture - dubois | 847 | 1_identitaires_france_turquie_imposture | | 2 | identitaires - france - lyonnais - musulmans - migrants | 96 | 2_identitaires_france_lyonnais_musulmans | | 3 | identitaires - france - banderole - djihadistes - montpellier | 92 | 3_identitaires_france_banderole_djihadistes | | 4 | identitaires - vraie - dubois - victoires - publications | 32 | 4_identitaires_vraie_dubois_victoires |
## 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: False * zeroshot_min_similarity: 0.7 * zeroshot_topic_list: None ## Framework versions * Numpy: 1.23.5 * HDBSCAN: 0.8.38.post1 * UMAP: 0.5.6 * Pandas: 2.2.2 * Scikit-Learn: 1.5.1 * Sentence-transformers: 3.0.1 * Transformers: 4.44.2 * Numba: 0.60.0 * Plotly: 5.24.0 * Python: 3.10.12