MARTINI_enrich_BERTopic_uch_uch_uch
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_uch_uch_uch")
topic_model.get_topic_info()
Topic overview
- Number of topics: 11
- Number of training documents: 1648
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | vakcinos - covid - 2021 - lietuva - euru | 21 | -1_vakcinos_covid_2021_lietuva |
| 0 | vakcinacija - vaers - pfizer - koronaviruso - injekcijos | 1084 | 0_vakcinacija_vaers_pfizer_koronaviruso |
| 1 | candida - bakteriju - insulino - produktus - hiperaktyviems | 120 | 1_candida_bakteriju_insulino_produktus |
| 2 | baltarusija - ukrainai - zelenskio - rusijos - amerikieciai | 102 | 2_baltarusija_ukrainai_zelenskio_rusijos |
| 3 | koronaviruso - pandemija - skaicius - imuniteta - dokumentas | 87 | 3_koronaviruso_pandemija_skaicius_imuniteta |
| 4 | globalistu - nibiru - revoliucijas - pandemija - 2050 | 60 | 4_globalistu_nibiru_revoliucijas_pandemija |
| 5 | kriptovaliutu - usd - rubli - rusija - banko | 53 | 5_kriptovaliutu_usd_rubli_rusija |
| 6 | tepineliai - susitikimo - neegzistuojanciu - bukstauta - raportuokime | 40 | 6_tepineliai_susitikimo_neegzistuojanciu_bukstauta |
| 7 | susitikimai - sunkiausias - mentalinio - plaukus - energijos | 36 | 7_susitikimai_sunkiausias_mentalinio_plaukus |
| 8 | gmo - bioinzinerijos - crispr - patentas - pomidorai | 24 | 8_gmo_bioinzinerijos_crispr_patentas |
| 9 | raskeviciau - konstitucija - ratifikavus - tolerancijos - bankiniai | 21 | 9_raskeviciau_konstitucija_ratifikavus_tolerancijos |
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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