BERTopic-transcripts

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("nataliecastro/BERTopic-transcripts")

topic_model.get_topic_info()

Topic overview

• Number of topics: 2
• Number of training documents: 4170

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
0	the - and - to - that - of	4149	0_the_and_to_that
1	music - and - to - the - of	21	1_music_and_to_the

Training hyperparameters

• calculate_probabilities: False
• language: english
• 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: 1.24.3
• HDBSCAN: 0.8.29
• UMAP: 0.5.6
• Pandas: 1.5.3
• Scikit-Learn: 1.2.2
• Sentence-transformers: 3.1.0
• Transformers: 4.44.2
• Numba: 0.57.0
• Plotly: 5.9.0
• Python: 3.10.12