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BERTopic_astrosenmovimiento

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("sdantonio/BERTopic_astrosenmovimiento")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 6
  • Number of training documents: 404
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 inenarrable - queridas - encuadrando - reiniciar - encapsulan 16 -1_inenarrable_queridas_encuadrando_reiniciar
0 genes - tardes - bellas - mercurio - venus 6 0_genes_tardes_bellas_mercurio
1 adentro - venus - mercurio - escorpio - suen 151 1_adentro_venus_mercurio_escorpio
2 bellas - venus - eclipse - comparto - pluto 129 2_bellas_venus_eclipse_comparto
3 bellas - mercurio - escorpio - venus - comparto 58 3_bellas_mercurio_escorpio_venus
4 historias - lxs - sinergia - bellas - venus 44 4_historias_lxs_sinergia_bellas

Training hyperparameters

  • calculate_probabilities: False
  • language: None
  • 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: 1.23.5
  • HDBSCAN: 0.8.38.post1
  • UMAP: 0.5.6
  • Pandas: 2.2.2
  • Scikit-Learn: 1.5.1
  • Sentence-transformers: 3.0.1
  • Transformers: 4.44.2
  • Numba: 0.60.0
  • Plotly: 5.24.0
  • Python: 3.10.12
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