MARTINI_enrich_BERTopic_docentesxlv
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_docentesxlv")
topic_model.get_topic_info()
Topic overview
- Number of topics: 11
- Number of training documents: 1223
Click here for an overview of all topics.
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | vacunados - pandemia - libertad - genocida - informacion | 21 | -1_vacunados_pandemia_libertad_genocida |
| 0 | seguirnos - mentiras - argentina - enemigos - organizadores | 833 | 0_seguirnos_mentiras_argentina_enemigos |
| 1 | muerto - vacunarse - noviembre - miocarditis - convulsiones | 54 | 1_muerto_vacunarse_noviembre_miocarditis |
| 2 | mascarillas - escuela - epidemia - declaracion - respirar | 50 | 2_mascarillas_escuela_epidemia_declaracion |
| 3 | mundialistas - desinformacion - bancos - blackrock - crisis | 47 | 3_mundialistas_desinformacion_bancos_blackrock |
| 4 | manifestaciones - policia - holanda - espana - corona | 41 | 4_manifestaciones_policia_holanda_espana |
| 5 | vacunados - mercola - escucharla - sobrevivir - radiacion | 40 | 5_vacunados_mercola_escucharla_sobrevivir |
| 6 | vacunados - covidiotas - contagiosa - variantes - nunca | 39 | 6_vacunados_covidiotas_contagiosa_variantes |
| 7 | vacunas - fallecidos - hospitalizaciones - efectos - informes | 35 | 7_vacunas_fallecidos_hospitalizaciones_efectos |
| 8 | adoctrinamiento - desobedezcamos - revolucionaria - empecemos - conseguirme | 33 | 8_adoctrinamiento_desobedezcamos_revolucionaria_empecemos |
| 9 | vacunar - argentina - judeosatanica - infanticidio - amenazas | 30 | 9_vacunar_argentina_judeosatanica_infanticidio |
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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