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MaximSIMO/
bertopic_openai_emb_model

bertopic

text-classification

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bertopic_openai_emb_model

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("MaximSIMO/bertopic_openai_emb_model")

topic_model.get_topic_info()

Topic overview

Number of topics: 3
Number of training documents: 100

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	Evening TV Programming	13	-1_Evening TV Programming
0	Elettrodotti e ambiente	15	0_Elettrodotti e ambiente
1	Political Tensions	72	1_Political Tensions

Training hyperparameters

calculate_probabilities: False
language: multilingual
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: 2.2.6
HDBSCAN: 0.8.41
UMAP: 0.5.11
Pandas: 2.3.3
Scikit-Learn: 1.7.2
Sentence-transformers: 5.2.2
Transformers: 5.1.0
Numba: 0.63.1
Plotly: 6.5.2
Python: 3.10.19