
# chat_topics

This is a [BERTopic](https://github.com/MaartenGr/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:

```python
from bertopic import BERTopic
topic_model = BERTopic.load("davanstrien/chat_topics")

topic_model.get_topic_info()
```

## Topic overview

* Number of topics: 75
* Number of training documents: 63530

<details>
  <summary>Click here for an overview of all topics.</summary>
  
  | Topic ID | Topic Keywords | Topic Frequency | Label | 
|----------|----------------|-----------------|-------| 
| -1 | provide - using - information - sure - help | 26 | -1_provide_using_information_sure | 
| 0 | openai - ai - chatgpt - assistant - language | 7837 | Generative AI | 
| 1 | anytime - welcome - assistance - helpful - thank | 1342 | 1_anytime_welcome_assistance_helpful | 
| 2 | quantum - particle - physics - particles - relativity | 778 | Physics | 
| 3 | story - lived - life - novel - felt | 569 | 3_story_lived_life_novel | 
| 4 | letter - sincerely - regards - email - dear | 516 | 4_letter_sincerely_regards_email | 
| 5 | rust - haskell - programming - java - languages | 504 | programming | 
| 6 | css - html - style - div - js | 494 | web programming | 
| 7 | linux - ubuntu - debian - fedora - install | 440 | 7_linux_ubuntu_debian_fedora | 
| 8 | recipe - bake - ingredients - baking - dough | 425 | 8_recipe_bake_ingredients_baking | 
| 9 | websocket - json - socket - api - discord | 425 | 9_websocket_json_socket_api | 
| 10 | communism - capitalism - marx - economic - economy | 424 | 10_communism_capitalism_marx_economic | 
| 11 | dog - pet - breed - breeds - pets | 408 | 11_dog_pet_breed_breeds | 
| 12 | philosophy - theological - philosophical - beliefs - consciousness | 394 | 12_philosophy_theological_philosophical_beliefs | 
| 13 | git - github - repository - software - commit | 381 | 13_git_github_repository_software | 
| 14 | music - songs - musical - lyrics - song | 370 | 14_music_songs_musical_lyrics | 
| 15 | devops - development - developers - industry - develop | 323 | 15_devops_development_developers_industry | 
| 16 | pythagorean - hypotenuse - triangle - math - sqrt | 302 | 16_pythagorean_hypotenuse_triangle_math | 
| 17 | eu - europe - economy - economic - war | 291 | 17_eu_europe_economy_economic | 
| 18 | sleep - asleep - bedtime - procrastination - depression | 280 | 18_sleep_asleep_bedtime_procrastination | 
| 19 | kramer - seinfeld - jerry - cafe - elaine | 279 | 19_kramer_seinfeld_jerry_cafe | 
| 20 | printing - prints - printer - print - printers | 276 | 20_printing_prints_printer_print | 
| 21 | influenza - flu - panic - symptoms - medical | 251 | 21_influenza_flu_panic_symptoms | 
| 22 | chess - chessboard - practice - strategy - learn | 242 | 22_chess_chessboard_practice_strategy | 
| 23 | algorithm - primes - array - integers - python | 240 | 23_algorithm_primes_array_integers | 
| 24 | youtube - viewers - media - google - streaming | 240 | 24_youtube_viewers_media_google | 
| 25 | poison - chemicals - powder - turpentine - smoke | 226 | 25_poison_chemicals_powder_turpentine | 
| 26 | monday - sunday - count_weekend_days - calendar - dates | 216 | 26_monday_sunday_count_weekend_days_calendar | 
| 27 | colors - colour - color - pigments - blue | 208 | 27_colors_colour_color_pigments | 
| 28 | roman - attila - rome - empire - warfare | 205 | 28_roman_attila_rome_empire | 
| 29 | investing - investments - investment - stocks - financial | 204 | 29_investing_investments_investment_stocks | 
| 30 | vocabulary - wordle - words - scrabble - word | 201 | 30_vocabulary_wordle_words_scrabble | 
| 31 | planets - sun - earth - planet - pluto | 198 | 31_planets_sun_earth_planet | 
| 32 | renewable - solar - electricity - energy - electrical | 190 | 32_renewable_solar_electricity_energy | 
| 33 | pygame - ball_radius - draw - circle - canvas | 181 | 33_pygame_ball_radius_draw_circle | 
| 34 | fishing - fish - boat - hiking - camping | 176 | 34_fishing_fish_boat_hiking | 
| 35 | gpus - gpu - motherboard - cpu - hardware | 162 | 35_gpus_gpu_motherboard_cpu | 
| 36 | hvac - remodeling - energy - kwh - housing | 159 | 36_hvac_remodeling_energy_kwh | 
| 37 | database - graphql - databases - postgresql - sql | 159 | 37_database_graphql_databases_postgresql | 
| 38 | información - significado - cómo - como - sistemas | 158 | 38_información_significado_cómo_como | 
| 39 | motherboard - pcie - gpu - bios - computer | 153 | 39_motherboard_pcie_gpu_bios | 
| 40 | crops - produce - planting - peppers - plants | 148 | 40_crops_produce_planting_peppers | 
| 41 | paintings - art - modernist - artists - modern | 148 | 41_paintings_art_modernist_artists | 
| 42 | workout - exercises - dumbbells - dumbbell - exercise | 147 | 42_workout_exercises_dumbbells_dumbbell | 
| 43 | climate - warming - pollution - environmental - emissions | 142 | 43_climate_warming_pollution_environmental | 
| 44 | coffee - espresso - brewing - tea - beans | 137 | 44_coffee_espresso_brewing_tea | 
| 45 | velocity - drag - acceleration - density - formula | 132 | 45_velocity_drag_acceleration_density | 
| 46 | woodchuck - woodchucks - units - kilogram - kilograms | 130 | 46_woodchuck_woodchucks_units_kilogram | 
| 47 | ascii - glyphs - hiragana - art - font | 129 | 47_ascii_glyphs_hiragana_art | 
| 48 | guitars - guitar - strings - guitarists - instrument | 127 | 48_guitars_guitar_strings_guitarists | 
| 49 | tallest - buildings - building - burj - khalifa | 114 | 49_tallest_buildings_building_burj | 
| 50 | flat - earth - curvature - spherical - tectonic | 111 | 50_flat_earth_curvature_spherical | 
| 51 | essay - awareness - understanding - being - be | 102 | 51_essay_awareness_understanding_being | 
| 52 | portals - ender - portal - obsidian - netherite | 102 | 52_portals_ender_portal_obsidian | 
| 53 | android - apple - phones - devices - vehicles | 101 | 53_android_apple_phones_devices | 
| 54 | fasting - dietary - diet - eating - metabolic | 101 | 54_fasting_dietary_diet_eating | 
| 55 | meditation - relief - pain - health - nociception | 99 | 55_meditation_relief_pain_health | 
| 56 | weather - forecast - forecasts - raining - precipitation | 95 | 56_weather_forecast_forecasts_raining | 
| 57 | president - presidents - presidency - constitution - biden | 94 | 57_president_presidents_presidency_constitution | 
| 58 | no - nope - yes - not - maybe | 94 | 58_no_nope_yes_not | 
| 59 | peregrine - airspeed - falcon - speed - bird | 90 | 59_peregrine_airspeed_falcon_speed | 
| 60 | crontab - cron - myscript - script - bash | 83 | 60_crontab_cron_myscript_script | 
| 61 | youtuber - streamer - ceo - musk - founder | 83 | 61_youtuber_streamer_ceo_musk | 
| 62 | layovers - flights - circumnavigate - layover - travel | 83 | 62_layovers_flights_circumnavigate_layover | 
| 63 | keyboards - keyboard - switches - qwerty - types | 83 | 63_keyboards_keyboard_switches_qwerty | 
| 64 | file_path_in_dir1 - file_path1 - csv_file - file_path_in_dir2 - file_path2 | 80 | 64_file_path_in_dir1_file_path1_csv_file_file_path_in_dir2 | 
| 65 | pele - maradona - lebron - ronaldo - nba | 76 | 65_pele_maradona_lebron_ronaldo | 
| 66 | alopecia - hairstyles - hairstyle - hair - scalp | 66 | 66_alopecia_hairstyles_hairstyle_hair | 
| 67 | nginx - docker - kubernetes - proxy_pass - nodeport | 65 | 67_nginx_docker_kubernetes_proxy_pass | 
| 68 | directories - directory - sudo - filesystem - folders | 62 | 68_directories_directory_sudo_filesystem | 
| 69 | gps - map - geocaching - maps - armenia | 52 | 69_gps_map_geocaching_maps | 
| 70 | meiosis - mitosis - fertilization - reproduction - ovulation | 51 | 70_meiosis_mitosis_fertilization_reproduction | 
| 71 | colleges - admissions - universities - campus - university | 43 | 71_colleges_admissions_universities_campus | 
| 72 | unicorns - unicorn - pony - ponies - mythical | 32 | 72_unicorns_unicorn_pony_ponies | 
| 73 | superpowers - abilities - superhero - superhuman - powers | 28 | 73_superpowers_abilities_superhero_superhuman |
  
</details>

## Training hyperparameters

* calculate_probabilities: False
* language: None
* low_memory: False
* min_topic_size: 20
* n_gram_range: (1, 1)
* nr_topics: 75
* seed_topic_list: None
* top_n_words: 10
* verbose: True

## Framework versions

* Numpy: 1.22.4
* HDBSCAN: 0.8.29
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.29.2
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.11
{"language": ["en"], "license": "mit", "library_name": "bertopic", "tags": ["bertopic"], "datasets": ["OpenAssistant/oasst1"], "pipeline_tag": "text-classification"}
bertopic text-classification en dataset:OpenAssistant/oasst1 license:mit has_space region:us
TAGS
#bertopic #text-classification #en #dataset-OpenAssistant/oasst1 #license-mit #has_space #region-us 

chat\_topics
============


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:


You can use the model as follows:


Topic overview
--------------


* Number of topics: 75
* Number of training documents: 63530



Click here for an overview of all topics.


Training hyperparameters
------------------------


* calculate\_probabilities: False
* language: None
* low\_memory: False
* min\_topic\_size: 20
* n\_gram\_range: (1, 1)
* nr\_topics: 75
* seed\_topic\_list: None
* top\_n\_words: 10
* verbose: True


Framework versions
------------------


* Numpy: 1.22.4
* HDBSCAN: 0.8.29
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.29.2
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.11



TAGS
#bertopic #text-classification #en #dataset-OpenAssistant/oasst1 #license-mit #has_space #region-us 
