jaria_topics

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("caiocof/jaria_topics")

topic_model.get_topic_info()

Topic overview

Number of topics: 2
Number of training documents: 206

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
0	de - do - da - no - que	182	0_de_do_da_no
1	legalidade - do - ait - da - princípio	24	1_legalidade_do_ait_da

Training hyperparameters

calculate_probabilities: False
language: portuguese
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: 1.26.4
HDBSCAN: 0.8.40
UMAP: 0.5.7
Pandas: 1.5.3
Scikit-Learn: 1.3.0
Sentence-transformers: 4.0.1
Transformers: 4.48.1
Numba: 0.59.1
Plotly: 5.22.0
Python: 3.12.4