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--- |
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tags: |
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- bertopic |
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library_name: bertopic |
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pipeline_tag: text-classification |
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--- |
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# MARTINI_enrich_BERTopic_joinmiFight |
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model. |
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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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## Usage |
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To use this model, please install BERTopic: |
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``` |
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pip install -U bertopic |
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``` |
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You can use the model as follows: |
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```python |
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from bertopic import BERTopic |
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topic_model = BERTopic.load("AIDA-UPM/MARTINI_enrich_BERTopic_joinmiFight") |
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topic_model.get_topic_info() |
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``` |
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## Topic overview |
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* Number of topics: 9 |
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* Number of training documents: 1033 |
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<details> |
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<summary>Click here for an overview of all topics.</summary> |
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| Topic ID | Topic Keywords | Topic Frequency | Label | |
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|----------|----------------|-----------------|-------| |
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| -1 | pfizer - vaxx - bioweapons - biden - 2021 | 21 | -1_pfizer_vaxx_bioweapons_biden | |
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| 0 | god - trump - freedoms - unrighteousness - warmongers | 586 | 0_god_trump_freedoms_unrighteousness | |
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| 1 | vaccinated - pfizer - injections - hospitalizations - 2021 | 120 | 1_vaccinated_pfizer_injections_hospitalizations | |
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| 2 | vaccine - mrna - injections - nanotechnologies - dr | 70 | 2_vaccine_mrna_injections_nanotechnologies | |
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| 3 | transhumanism - darpa - neuralink - chatgpt - blinken | 60 | 3_transhumanism_darpa_neuralink_chatgpt | |
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| 4 | pfizer - biowarfare - dod - prosecuting - liability | 55 | 4_pfizer_biowarfare_dod_prosecuting | |
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| 5 | fauci - karen - whistleblower - livestream - mikovits | 51 | 5_fauci_karen_whistleblower_livestream | |
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| 6 | sars - bioweapons - vaccine - darpa - aerosolized | 38 | 6_sars_bioweapons_vaccine_darpa | |
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| 7 | fauci - sarscov - funded - wuhan - huff | 32 | 7_fauci_sarscov_funded_wuhan | |
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</details> |
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## Training hyperparameters |
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* calculate_probabilities: True |
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* language: None |
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* low_memory: False |
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* min_topic_size: 10 |
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* n_gram_range: (1, 1) |
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* nr_topics: None |
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* seed_topic_list: None |
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* top_n_words: 10 |
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* verbose: False |
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* zeroshot_min_similarity: 0.7 |
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* zeroshot_topic_list: None |
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## Framework versions |
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* Numpy: 1.26.4 |
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* HDBSCAN: 0.8.40 |
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* UMAP: 0.5.7 |
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* Pandas: 2.2.3 |
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* Scikit-Learn: 1.5.2 |
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* Sentence-transformers: 3.3.1 |
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* Transformers: 4.46.3 |
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* Numba: 0.60.0 |
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* Plotly: 5.24.1 |
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* Python: 3.10.12 |
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