BERTopic_ZoroKanalas

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_ZoroKanalas")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 19
  • Number of training documents: 7483
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 kazakhstanas - iregistruotos - paryziuje - lionel - zelenkiui 11 -1_kazakhstanas_iregistruotos_paryziuje_lionel
0 pries - rusijos - ukrainos - rusija - eme 96 0_pries_rusijos_ukrainos_rusija
1 maikelis - isvede - joe - londono - londonas 6689 1_maikelis_isvede_joe_londono
2 jk - skiepus - statula - slava - lukas 194 2_jk_skiepus_statula_slava
3 varlyte - parsidavele - gates - vakcinos - utilizacija 79 3_varlyte_parsidavele_gates_vakcinos
4 snikerio - tortas - triufeliai - ingridijentai - bic 63 4_snikerio_tortas_triufeliai_ingridijentai
5 vokietija - - - - 45 5_vokietija___
6 londonas - jk - anglija - policija - gejukai 43 6_londonas_jk_anglija_policija
7 rusija - jav - donald - vilnius - brazilija 41 7_rusija_jav_donald_vilnius
8 tikekime - zelenskis - kinijos - aveles - cirkas 38 8_tikekime_zelenskis_kinijos_aveles
9 pasaulinio - cukrus - fluoras - 5g - eismas 29 9_pasaulinio_cukrus_fluoras_5g
10 madridas - ispanija - 03 - 2023 - 28 10_madridas_ispanija_03_2023
11 zaporoz - zelenkis - - - 24 11_zaporoz_zelenkis__
12 sniegas - vokietija - lapkric - aliaskoje - atostogos 24 12_sniegas_vokietija_lapkric_aliaskoje
13 tikintis - aveles - avys - vakcinos - klausas 21 13_tikintis_aveles_avys_vakcinos
14 - - - - 18 14____
15 - - - - 15 15____
16 chemtreilai - ampinjonai - chemtrailai - barbe - psr 13 16_chemtreilai_ampinjonai_chemtrailai_barbe
17 zelenskis - - - - 12 17_zelenskis___

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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