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:

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