MARTINI_enrich_BERTopic_bagelsandshadeshow

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("AIDA-UPM/MARTINI_enrich_BERTopic_bagelsandshadeshow")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 10
  • Number of training documents: 1134
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 trump - israel - covid - beast - test 22 -1_trump_israel_covid_beast
0 luciferians - antichrist - satanic - baal - savior 499 0_luciferians_antichrist_satanic_baal
1 fires - explosion - evacuated - propane - louisiana 146 1_fires_explosion_evacuated_propane
2 vaccinated - pfizer - shots - myocarditis - lethal 121 2_vaccinated_pfizer_shots_myocarditis
3 floods - torrential - thunderstorms - sandstorm - mecca 120 3_floods_torrential_thunderstorms_sandstorm
4 conspiracy - everything - seizing - manipulated - crash 66 4_conspiracy_everything_seizing_manipulated
5 cashless - cbdc - mastercard - citizens - currencies 56 5_cashless_cbdc_mastercard_citizens
6 trafficked - pedophiles - hotline - survivors - shay 48 6_trafficked_pedophiles_hotline_survivors
7 holograms - haarp - luciferans - activated - satellites 32 7_holograms_haarp_luciferans_activated
8 gunshots - rioting - officers - columbus - victim 24 8_gunshots_rioting_officers_columbus

Training hyperparameters

  • calculate_probabilities: True
  • 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: 1.26.4
  • HDBSCAN: 0.8.40
  • UMAP: 0.5.7
  • Pandas: 2.2.3
  • Scikit-Learn: 1.5.2
  • Sentence-transformers: 3.3.1
  • Transformers: 4.46.3
  • Numba: 0.60.0
  • Plotly: 5.24.1
  • Python: 3.10.12
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