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---
pipeline_tag: text-classification
---
## Usage
To use this model, please install BERTopic:
pip install bertopic
You can use the model as follows:
from bertopic import BERTopic
topic_model = BERTopic.load("Alprocco/semi_supervised_bertopic")
topic_model.get_topic_info()
## Topic overview
Number of topics: 30
Training hyperparameters
calculate_probabilities: False
language: multilingual
low_memory: False
min_topic_size: 10
n_gram_range: (1, 1)
nr_topics: 30
top_n_words: 10
verbose: True
Note: When saving the model, make sure to also keep track of the versions of dependencies and Python used.
Loading and saving the model should be done using the same dependencies and Python.
Moreover, models saved in one version of BERTopic are not guaranteed to load in other versions.
## Framework versions
bertopic 0.15.0
Numpy: 1.24.4
HDBSCAN: 0.8.33
UMAP: 0.5.4
Pandas: 2.0.3
Scikit-Learn: 1.0.2
Sentence-transformers: 2.2.2
Transformers: 4.33.2
Numba: 0.58.0
Plotly: 5.17.0
Python: 3.8.10 |