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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_thepeopleslawyerchannel |
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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_thepeopleslawyerchannel") |
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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: 26 |
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* Number of training documents: 2705 |
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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 | unvaccinated - mandates - pfizer - 2021 - freedom | 20 | -1_unvaccinated_mandates_pfizer_2021 | |
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| 0 | vaers - myocarditis - 2022 - died - footballer | 1183 | 0_vaers_myocarditis_2022_died | |
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| 1 | donetsk - russians - zelensky - ukrainian - sanctions | 206 | 1_donetsk_russians_zelensky_ukrainian | |
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| 2 | awakening - indoctrination - reality - freedom - god | 190 | 2_awakening_indoctrination_reality_freedom | |
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| 3 | pandemics - amendments - sovereignty - parliament - geneva | 139 | 3_pandemics_amendments_sovereignty_parliament | |
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| 4 | cashless - banknotes - debit - wallet - rbnz | 100 | 4_cashless_banknotes_debit_wallet | |
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| 5 | alarmists - climatologist - thunberg - greenland - co2 | 94 | 5_alarmists_climatologist_thunberg_greenland | |
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| 6 | conspirach - msnbc - titanic - instagrammable - download | 92 | 6_conspirach_msnbc_titanic_instagrammable | |
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| 7 | trump - democrats - gabbard - warmongers - overthrow | 77 | 7_trump_democrats_gabbard_warmongers | |
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| 8 | millionlightpaperandleaflet - berkshirefreedom - canterbury - boards - yellow | 55 | 8_millionlightpaperandleaflet_berkshirefreedom_canterbury_boards | |
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| 9 | treasury - trillions - bankruptcy - blackrock - lockdown | 54 | 9_treasury_trillions_bankruptcy_blackrock | |
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| 10 | schooling - indoctrination - pedophiles - stopworldcontrol - prisons | 50 | 10_schooling_indoctrination_pedophiles_stopworldcontrol | |
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| 11 | vaxxed - thimerosal - adjuvants - injected - grafene | 49 | 11_vaxxed_thimerosal_adjuvants_injected | |
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| 12 | thepeopleslawyeruk - tpl - cornwall - plumstead - event | 44 | 12_thepeopleslawyeruk_tpl_cornwall_plumstead | |
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| 13 | vaccine - mhra - broadyorkshirelaw - constables - victims | 42 | 13_vaccine_mhra_broadyorkshirelaw_constables | |
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| 14 | trudeau - convoys - dictatorship - protesters - romania | 39 | 14_trudeau_convoys_dictatorship_protesters | |
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| 15 | hamas - zionists - matisyahu - israelis - haifa | 35 | 15_hamas_zionists_matisyahu_israelis | |
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| 16 | bolsonaro - brasilia - moraes - protesters - inviolable | 34 | 16_bolsonaro_brasilia_moraes_protesters | |
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| 17 | radiation - fluorescent - antenna - 5g - milliwatts | 33 | 17_radiation_fluorescent_antenna_5g | |
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| 18 | parliament - petition - deaths - saveoursovereignty - wales | 31 | 18_parliament_petition_deaths_saveoursovereignty | |
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| 19 | gmos - additives - edible - worms - nuts | 29 | 19_gmos_additives_edible_worms | |
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| 20 | immigrants - texas - billion - invading - border | 27 | 20_immigrants_texas_billion_invading | |
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| 21 | sarscov - peramivir - parainfluenza - adenovirus - swab | 21 | 21_sarscov_peramivir_parainfluenza_adenovirus | |
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| 22 | chemtrails - contrails - spraying - fog - pilot | 21 | 22_chemtrails_contrails_spraying_fog | |
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| 23 | britishlionsforfreedom - worldwidedemonstration - cardiff - 2023 - july | 20 | 23_britishlionsforfreedom_worldwidedemonstration_cardiff_2023 | |
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| 24 | electricity - billing - petrol - meters - fraudsters | 20 | 24_electricity_billing_petrol_meters | |
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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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