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potloc-topic-model

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("joshEm/potloc-topic-model")

topic_model.get_topic_info()

Topic overview

  • Number of topics: 132
  • Number of training documents: 10000
Click here for an overview of all topics.
Topic ID Topic Keywords Topic Frequency Label
-1 the - in - and - of - to 10 -1_the_in_and_of
0 computer - yahoo - windows - click - can 3344 0_computer_yahoo_windows_click
1 god - jesus - bible - of - believe 958 1_god_jesus_bible_of
2 bush - president - war - iraq - us 487 2_bush_president_war_iraq
3 court - job - to - for - jail 387 3_court_job_to_for
4 equation - solve - number - answer - numbers 208 4_equation_solve_number_answer
5 foreheadnheadon - directly - apply - skin - ear 162 5_foreheadnheadon_directly_apply_skin
6 song - lyrics - me - oh - music 130 6_song_lyrics_me_oh
7 degree - school - university - college - courses 123 7_degree_school_university_college
8 credit - account - mortgage - bank - loan 122 8_credit_account_mortgage_bank
9 music - song - songs - rock - favorite 111 9_music_song_songs_rock
10 friends - meet - friend - looking - woman 109 10_friends_meet_friend_looking
11 sex - orgasm - sexual - ejaculation - men 95 11_sex_orgasm_sexual_ejaculation
12 where - ebay - buy - shirt - find 94 12_where_ebay_buy_shirt
13 usa - cup - world - win - team 90 13_usa_cup_world_win
14 illegal - immigrants - mexico - illegals - immigration 81 14_illegal_immigrants_mexico_illegals
15 ball - sport - bowling - play - tennis 80 15_ball_sport_bowling_play
16 plants - plant - whales - species - seals 78 16_plants_plant_whales_species
17 man - joke - said - he - she 77 17_man_joke_said_he
18 him - he - me - guy - but 72 18_him_he_me_guy
19 period - doctor - periods - pregnant - pregnancy 65 19_period_doctor_periods_pregnant
20 study - math - test - sat - practice 64 20_study_math_test_sat
21 water - solution - moles - reaction - grams 64 21_water_solution_moles_reaction
22 flag - 1918 - of - was - the 63 22_flag_1918_of_was
23 means - french - mi - word - mean 63 23_means_french_mi_word
24 baseball - player - he - sox - pitcher 62 24_baseball_player_he_sox
25 girls - guys - men - girl - women 60 25_girls_guys_men_girl
26 questions - points - question - bored - answers 60 26_questions_points_question_bored
27 sleep - feel - hours - depression - you 57 27_sleep_feel_hours_depression
28 dna - genetic - blood - gene - cells 54 28_dna_genetic_blood_gene
29 english - language - french - learn - spanish 54 29_english_language_french_learn
30 search - find - name - looking - address 53 30_search_find_name_looking
31 word - winter - words - letters - letter 53 31_word_winter_words_letters
32 weight - calories - fat - diet - eat 52 32_weight_calories_fat_diet
33 bowl - game - qb - team - usc 47 33_bowl_game_qb_team
34 moon - time - horizon - day - sun 47 34_moon_time_horizon_day
35 wwe - guerrero - tna - diva - cena 45 35_wwe_guerrero_tna_diva
36 her - mom - gift - she - ideas 44 36_her_mom_gift_she
37 him - he - sister - my - his 44 37_him_he_sister_my
38 book - books - read - harlem - beard 43 38_book_books_read_harlem
39 color - blue - sky - light - colors 43 39_color_blue_sky_light
40 tax - taxes - unemployment - state - income 42 40_tax_taxes_unemployment_state
41 alamo - movie - movies - trilogy - aka 42 41_alamo_movie_movies_trilogy
42 show - watch - anime - episodes - tv 42 42_show_watch_anime_episodes
43 insurance - health - disability - help - for 42 43_insurance_health_disability_help
44 girl - her - she - likes - ask 42 44_girl_her_she_likes
45 navy - military - army - marine - marines 41 45_navy_military_army_marine
46 white - black - racist - blacks - racism 40 46_white_black_racist_blacks
47 cheat - spouse - wife - her - she 40 47_cheat_spouse_wife_her
48 he - him - likes - guy - me 39 48_he_him_likes_guy
49 visa - passport - birth - us - citizen 38 49_visa_passport_birth_us
50 marijuana - drug - weed - opium - test 37 50_marijuana_drug_weed_opium
51 velocity - force - angle - cm - triangle 37 51_velocity_force_angle_cm
52 cup - championship - world - player - euro 36 52_cup_championship_world_player
53 nascar - racing - fight - gordon - sport 33 53_nascar_racing_fight_gordon
54 celebrities - tom - celebrity - her - jolie 32 54_celebrities_tom_celebrity_her
55 cricket - india - batsman - dravid - indian 31 55_cricket_india_batsman_dravid
56 weight - eat - skinny - fat - healthy 30 56_weight_eat_skinny_fat
57 eye - lenses - astigmatism - eyes - glasses 30 57_eye_lenses_astigmatism_eyes
58 people - yourself - person - others - confidence 29 58_people_yourself_person_others
59 stock - fund - shares - mutual - market 29 59_stock_fund_shares_mutual
60 arsenal - liverpool - league - fans - celtic 29 60_arsenal_liverpool_league_fans
61 warming - global - climate - ice - snow 29 61_warming_global_climate_ice
62 her - she - friend - friends - me 28 62_her_she_friend_friends
63 wave - frequency - electromagnetic - radar - antenna 28 63_wave_frequency_electromagnetic_radar
64 dream - dreams - my - elevator - was 27 64_dream_dreams_my_elevator
65 gauge - bullet - caliber - gun - barrel 27 65_gauge_bullet_caliber_gun
66 pain - knee - elbow - tennis - shoulder 27 66_pain_knee_elbow_tennis
67 beach - trail - resort - appalachian - shaw 26 67_beach_trail_resort_appalachian
68 scam - home - quixtar - money - survey 25 68_scam_home_quixtar_money
69 business - sell - idea - start - money 25 69_business_sell_idea_start
70 tv - watch - channels - espn - cup 25 70_tv_watch_channels_espn
71 abs - muscles - exercises - reps - muscle 25 71_abs_muscles_exercises_reps
72 hair - shave - cut - pubic - trim 25 72_hair_shave_cut_pubic
73 psychic - divination - astrology - cards - tarot 25 73_psychic_divination_astrology_cards
74 number - phone - code - address - area 24 74_number_phone_code_address
75 was - my - hit - ever - freezer 24 75_was_my_hit_ever
76 trailers - trailer - dvd - media - wmp 24 76_trailers_trailer_dvd_media
77 penis - condom - size - sex - inches 24 77_penis_condom_size_sex
78 love - person - beloved - live - we 24 78_love_person_beloved_live
79 war - world - countries - soviet - were 24 79_war_world_countries_soviet
80 de - le - la - et - les 24 80_de_le_la_et
81 job - jobs - guard - where - work 24 81_job_jobs_guard_where
82 christmas - thanksgiving - holidays - celebrate - tree 24 82_christmas_thanksgiving_holidays_celebrate
83 hepatitis - pneumonia - infections - vaccination - link 23 83_hepatitis_pneumonia_infections_vaccination
84 peanuts - ibs - may - heartburn - bowel 22 84_peanuts_ibs_may_heartburn
85 name - sarah - named - pronounced - my 21 85_name_sarah_named_pronounced
86 kids - he - husband - him - cheated 20 86_kids_he_husband_him
87 gas - oil - energy - kingdom - 2006 19 87_gas_oil_energy_kingdom
88 taller - tall - height - grow - short 19 88_taller_tall_height_grow
89 estate - property - heirs - lien - damages 19 89_estate_property_heirs_lien
90 aluminum - 68 - element - 212 - metal 18 90_aluminum_68_element_212
91 organization - management - organizational - behavior - leadership 18 91_organization_management_organizational_behavior
92 melatonin - medication - effects - dosage - zofran 18 92_melatonin_medication_effects_dosage
93 smoking - quit - smoke - smoked - session 17 93_smoking_quit_smoke_smoked
94 nba - referees - game - heat - win 17 94_nba_referees_game_heat
95 superman - doom - hero - vs - super 17 95_superman_doom_hero_vs
96 skateboarding - skateboard - snowboard - snowboarding - gymnastics 17 96_skateboarding_skateboard_snowboard_snowboarding
97 electron - quarks - neutrons - antimatter - particle 16 97_electron_quarks_neutrons_antimatter
98 happy - happiness - life - rushhour - secret 16 98_happy_happiness_life_rushhour
99 fart - farting - gas - embarrassing - flatus 16 99_fart_farting_gas_embarrassing
100 teeth - tooth - dentist - gums - braces 16 100_teeth_tooth_dentist_gums
101 scorpio - zodiac - libra - signs - cancers 16 101_scorpio_zodiac_libra_signs
102 dog - wolf - sheep - horse - animal 16 102_dog_wolf_sheep_horse
103 hiv - aids - virus - infected - blood 16 103_hiv_aids_virus_infected
104 thanked - poem - poetry - she - were 15 104_thanked_poem_poetry_she
105 force - motion - mass - momentum - rocket 15 105_force_motion_mass_momentum
106 minister - president - kagame - prime - natchaba 15 106_minister_president_kagame_prime
107 kiss - kissing - lips - gently - tongue 15 107_kiss_kissing_lips_gently
108 pictures - photos - google - site - find 15 108_pictures_photos_google_site
109 dating - age - old - young - 19 14 109_dating_age_old_young
110 ebay - sell - smc - selling - products 14 110_ebay_sell_smc_selling
111 planets - sun - stars - star - earth 14 111_planets_sun_stars_star
112 imports - trade - importing - oil - mobil 14 112_imports_trade_importing_oil
113 questions - question - politics - reported - answers 14 113_questions_question_politics_reported
114 gay - crackle - snap - girlfriend - marry 14 114_gay_crackle_snap_girlfriend
115 gravity - sun - earth - rotating - force 13 115_gravity_sun_earth_rotating
116 weaknesses - abt - strengths - interview - job 13 116_weaknesses_abt_strengths_interview
117 love - eachother - fall - forget - deeply 13 117_love_eachother_fall_forget
118 animals - pets - tv - cage - communicate 13 118_animals_pets_tv_cage
119 flax - yogurt - nonfat - health - healthy 13 119_flax_yogurt_nonfat_health
120 grants - grant - business - federal - entrepreneurs 13 120_grants_grant_business_federal
121 idol - american - chris - win - favorite 12 121_idol_american_chris_win
122 clubs - golf - hit - irons - iron 12 122_clubs_golf_hit_irons
123 lottery - scam - scammer - money - international 12 123_lottery_scam_scammer_money
124 address - email - presale - bart - michaels 12 124_address_email_presale_bart
125 jones - her - she - stargate - reynolds 11 125_jones_her_she_stargate
126 data - product - analysis - regression - marketing 11 126_data_product_analysis_regression
127 cancer - cure - tumor - parasite - cancers 11 127_cancer_cure_tumor_parasite
128 nba - paul - team - redick - kobe 11 128_nba_paul_team_redick
129 autism - autistic - homeschooling - child - she 10 129_autism_autistic_homeschooling_child
130 seller - nike - soccer - jersey - dynamo 10 130_seller_nike_soccer_jersey

Training hyperparameters

  • calculate_probabilities: False
  • language: english
  • 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: 1.23.5
  • HDBSCAN: 0.8.33
  • UMAP: 0.5.5
  • Pandas: 1.5.3
  • Scikit-Learn: 1.2.2
  • Sentence-transformers: 2.2.2
  • Transformers: 4.35.2
  • Numba: 0.58.1
  • Plotly: 5.15.0
  • Python: 3.10.12
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