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sdantonio/
BERTopic_generationidentitaire

bertopic

text-classification

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BERTopic_generationidentitaire

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:

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