MARTINI_enrich_BERTopic_redlistupdatesuk

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_redlistupdatesuk")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 11
  • Number of training documents: 789
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 covid - freedom - ukraine - everyone - telegram 22 -1_covid_freedom_ukraine_everyone
0 novavax - vaccinated - injections - bivalent - 2021 365 0_novavax_vaccinated_injections_bivalent
1 rallies - wokingham - wrldwide - free - leaflets 117 1_rallies_wokingham_wrldwide_free
2 amendments - pandemic - sovereignty - geneva - misinformation 59 2_amendments_pandemic_sovereignty_geneva
3 ukcolumn - livestream - 1pm - unmonitored - july 56 3_ukcolumn_livestream_1pm_unmonitored
4 brainwashed - davos - noory - influence - communism 44 4_brainwashed_davos_noory_influence
5 cashless - card - trains - natwest - closes 29 5_cashless_card_trains_natwest
6 nhs - doctors - britain - davies - artificial 25 6_nhs_doctors_britain_davies
7 ofcom - legislating - censorious - privacy - safer 24 7_ofcom_legislating_censorious_privacy
8 london - thetford - councillors - emissions - mile 24 8_london_thetford_councillors_emissions
9 britcoin - biometrics - identities - passport - parliament 24 9_britcoin_biometrics_identities_passport

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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