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MARTINI_enrich_BERTopic_Ryan_Cole
AIDA-UPM/MARTINI_enrich_BERTopic_Ryan_Cole
MARTINI_enrich_BERTopic_Ryan_Cole is a text classification model from AIDA-UPM. Use it when you need a label for a piece of text. It is set up for bertopic.
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.
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At a glance
- Task
- Text Classification
- Library
- bertopic
- Access
- Public
- Created
- Jan 14, 2025
- Updated
- Jan 14, 2025
- SHA
- 171b16b8
Try a prompt
Model card
From the Hugging Face model README
MARTINI_enrich_BERTopic_Ryan_Cole
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_Ryan_Cole")
topic_model.get_topic_info()
Topic overview
- Number of topics: 9
- Number of training documents: 649
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | pfizer - vaccinated - shots - mccullough - deaths | 23 | -1_pfizer_vaccinated_shots_mccullough |
| 0 | conspirators - cepi - rockefeller - doctors - world | 371 | 0_conspirators_cepi_rockefeller_doctors |
| 1 | novavax - oncologist - mutated - biontech - makis | 52 | 1_novavax_oncologist_mutated_biontech |
| 2 | myocarditis - clots - mrna - deadly - pathologist | 51 | 2_myocarditis_clots_mrna_deadly |
| 3 | fauci - redfield - manipulated - reveal - ralph | 44 | 3_fauci_redfield_manipulated_reveal |
| 4 | unvaccinated - rfk - toxoid - safer - sued | 31 | 4_unvaccinated_rfk_toxoid_safer |
| 5 | ivermectin - hydroxychloroquine - penicillin - miracle - overdose | 27 | 5_ivermectin_hydroxychloroquine_penicillin_miracle |
| 6 | vaccinated - deaths - lancet - c19 - australia | 27 | 6_vaccinated_deaths_lancet_c19 |
| 7 | reinfection - influenza - masks - chemoprophylaxis - researchers | 23 | 7_reinfection_influenza_masks_chemoprophylaxis |
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
- Task
- Text Classification
- Library
- bertopic
- Created
- Jan 14, 2025
- Updated
- Jan 14, 2025