Add BERTopic model
Browse files- README.md +128 -0
- config.json +15 -0
- topic_embeddings.safetensors +3 -0
- topics.json +6004 -0
README.md
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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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# cnn_dailymail_55555_3000_1500_train
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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("KingKazma/cnn_dailymail_55555_3000_1500_train")
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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: 61
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* Number of training documents: 3000
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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 | said - one - year - people - mr | 10 | -1_said_one_year_people |
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| 0 | league - game - player - cup - goal | 961 | 0_league_game_player_cup |
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| 1 | police - death - said - murder - family | 313 | 1_police_death_said_murder |
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| 2 | obama - republican - senate - president - republicans | 182 | 2_obama_republican_senate_president |
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| 3 | fashion - hair - look - makeup - brand | 91 | 3_fashion_hair_look_makeup |
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| 4 | dog - animal - cat - bird - pet | 69 | 4_dog_animal_cat_bird |
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| 5 | syria - isis - syrian - iraq - fighter | 54 | 5_syria_isis_syrian_iraq |
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| 6 | mexico - said - cuba - president - cartel | 53 | 6_mexico_said_cuba_president |
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| 7 | police - court - cash - jailed - said | 53 | 7_police_court_cash_jailed |
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| 8 | space - nasa - mars - planet - earth | 51 | 8_space_nasa_mars_planet |
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| 9 | property - house - price - room - london | 48 | 9_property_house_price_room |
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| 10 | patient - hospital - nhs - doctor - cancer | 48 | 10_patient_hospital_nhs_doctor |
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| 11 | tax - bank - minister - mr - pay | 46 | 11_tax_bank_minister_mr |
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| 12 | car - fire - crash - bus - train | 45 | 12_car_fire_crash_bus |
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| 13 | milk - food - raw - restaurant - chocolate | 44 | 13_milk_food_raw_restaurant |
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| 14 | gold - olympic - horse - race - medal | 36 | 14_gold_olympic_horse_race |
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| 15 | album - song - joel - music - show | 35 | 15_album_song_joel_music |
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| 16 | show - film - movie - award - les | 35 | 16_show_film_movie_award |
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| 17 | baby - born - hospital - birth - pregnancy | 34 | 17_baby_born_hospital_birth |
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| 18 | prince - queen - royal - william - duchess | 31 | 18_prince_queen_royal_william |
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| 19 | chinese - china - bo - beijing - chen | 30 | 19_chinese_china_bo_beijing |
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| 20 | labour - mr - party - ukip - miliband | 30 | 20_labour_mr_party_ukip |
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| 21 | school - student - teacher - book - fraternity | 29 | 21_school_student_teacher_book |
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| 22 | somalia - dala - african - alshabaab - mali | 28 | 22_somalia_dala_african_alshabaab |
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| 23 | ukraine - russian - russia - putin - moscow | 26 | 23_ukraine_russian_russia_putin |
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| 24 | woods - golf - golfer - hole - round | 26 | 24_woods_golf_golfer_hole |
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| 25 | sterling - nba - clippers - donald - said | 26 | 25_sterling_nba_clippers_donald |
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| 26 | found - scientist - stonehenge - researcher - frog | 26 | 26_found_scientist_stonehenge_researcher |
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| 27 | apple - iphone - apples - phone - device | 24 | 27_apple_iphone_apples_phone |
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| 28 | formula - race - schumacher - prix - ecclestone | 23 | 28_formula_race_schumacher_prix |
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| 29 | ebola - virus - outbreak - health - vaccine | 22 | 29_ebola_virus_outbreak_health |
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| 30 | church - pope - priest - francis - vatican | 21 | 30_church_pope_priest_francis |
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| 31 | sharapova - open - wimbledon - tennis - slam | 21 | 31_sharapova_open_wimbledon_tennis |
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| 32 | pakistani - pakistan - taliban - musharraf - afghanistan | 21 | 32_pakistani_pakistan_taliban_musharraf |
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| 33 | storm - weather - tornado - water - rain | 21 | 33_storm_weather_tornado_water |
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| 34 | north - korea - korean - kim - south | 21 | 34_north_korea_korean_kim |
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| 35 | war - medal - soldier - army - afghanistan | 21 | 35_war_medal_soldier_army |
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| 36 | marijuana - cigarette - alcohol - drug - smoking | 20 | 36_marijuana_cigarette_alcohol_drug |
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| 37 | internet - google - user - facebook - online | 19 | 37_internet_google_user_facebook |
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| 38 | plane - flight - crash - passenger - airport | 19 | 38_plane_flight_crash_passenger |
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| 39 | weight - diet - fat - stone - food | 18 | 39_weight_diet_fat_stone |
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| 40 | israeli - israel - gaza - hamas - palestinian | 17 | 40_israeli_israel_gaza_hamas |
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| 41 | beach - art - resort - festival - painting | 17 | 41_beach_art_resort_festival |
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| 42 | petraeus - cia - broadwell - justice - fbi | 17 | 42_petraeus_cia_broadwell_justice |
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| 43 | garner - wilson - officer - police - black | 16 | 43_garner_wilson_officer_police |
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| 44 | ship - cruise - ships - crew - pirate | 16 | 44_ship_cruise_ships_crew |
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| 45 | nfl - patriots - rice - seahawks - chris | 15 | 45_nfl_patriots_rice_seahawks |
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| 46 | dolphin - sea - creature - cuttlefish - fisherman | 14 | 46_dolphin_sea_creature_cuttlefish |
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| 47 | weather - rain - winter - temperature - warm | 14 | 47_weather_rain_winter_temperature |
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| 48 | mandela - african - africa - south - mandelas | 14 | 48_mandela_african_africa_south |
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| 49 | disney - snow - million - wars - movie | 14 | 49_disney_snow_million_wars |
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| 50 | price - bag - plastic - cent - energy | 13 | 50_price_bag_plastic_cent |
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| 51 | spartan - cliff - parachute - matthew - obstacle | 12 | 51_spartan_cliff_parachute_matthew |
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| 52 | zoo - panda - cub - giraffe - park | 12 | 52_zoo_panda_cub_giraffe |
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| 53 | iran - iranian - irans - ahmadinejad - nuclear | 12 | 53_iran_iranian_irans_ahmadinejad |
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| 54 | bin - laden - us - qaeda - al | 12 | 54_bin_laden_us_qaeda |
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| 55 | crocodile - snake - python - bascoules - alligator | 12 | 55_crocodile_snake_python_bascoules |
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| 56 | woman - ivf - men - dna - fertility | 11 | 56_woman_ivf_men_dna |
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| 57 | driver - driving - police - meracle - text | 11 | 57_driver_driving_police_meracle |
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| 58 | mitchell - mr - evans - mp - gate | 10 | 58_mitchell_mr_evans_mp |
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| 59 | france - police - mosque - salah - donetsk | 10 | 59_france_police_mosque_salah |
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</details>
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## Training hyperparameters
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* calculate_probabilities: True
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* language: english
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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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## Framework versions
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* Numpy: 1.22.4
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* HDBSCAN: 0.8.33
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* UMAP: 0.5.3
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* Pandas: 1.5.3
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* Scikit-Learn: 1.2.2
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* Sentence-transformers: 2.2.2
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* Transformers: 4.31.0
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* Numba: 0.56.4
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* Plotly: 5.13.1
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* Python: 3.10.6
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config.json
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{
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"calculate_probabilities": true,
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"language": "english",
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"low_memory": false,
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"min_topic_size": 10,
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"n_gram_range": [
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1,
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1
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],
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"nr_topics": null,
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"seed_topic_list": null,
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"top_n_words": 10,
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"verbose": false,
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
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}
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topic_embeddings.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d9d38f5278197518d10ad0ac61b8538d052b831ba7e9fb413ef11ff826f788a9
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size 93784
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topics.json
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