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nataliecastro/
BERTopic-transcripts

bertopic

text-classification

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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:

python

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