yelpreview_base / README.md

Add BERTopic model

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	---
	tags:
	- bertopic
	library_name: bertopic
	pipeline_tag: text-classification
	---

	# yelpreview_base

	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("Ayomidedeji/yelpreview_base")

	topic_model.get_topic_info()
	```

	## Topic overview

	* Number of topics: 98
	* Number of training documents: 10000

	<details>
	<summary>Click here for an overview of all topics.</summary>

	\| Topic ID \| Topic Keywords \| Topic Frequency \| Label \|
	\|----------\|----------------\|-----------------\|-------\|
	\| -1 \| food - good - place - great - like \| 10 \| -1_food_good_place_great \|
	\| 0 \| mexican - tacos - salsa - burrito - food \| 3827 \| 0_mexican_tacos_salsa_burrito \|
	\| 1 \| pizza - crust - pizzas - good - wait \| 705 \| 1_pizza_crust_pizzas_good \|
	\| 2 \| bar - music - drinks - night - place \| 393 \| 2_bar_music_drinks_night \|
	\| 3 \| burger - fries - burgers - good - like \| 288 \| 3_burger_fries_burgers_good \|
	\| 4 \| ordered - just - bread - good - chicken \| 275 \| 4_ordered_just_bread_good \|
	\| 5 \| sushi - roll - rolls - happy hour - happy \| 261 \| 5_sushi_roll_rolls_happy hour \|
	\| 6 \| scottsdale - place - great - bar - food \| 191 \| 6_scottsdale_place_great_bar \|
	\| 7 \| coffee - starbucks - coffee shop - shop - espresso \| 190 \| 7_coffee_starbucks_coffee shop_shop \|
	\| 8 \| hotel - pool - room - stay - resort \| 186 \| 8_hotel_pool_room_stay \|
	\| 9 \| minutes - table - server - asked - came \| 183 \| 9_minutes_table_server_asked \|
	\| 10 \| chinese - chinese food - food - asian - china \| 145 \| 10_chinese_chinese food_food_asian \|
	\| 11 \| thai - pad - curry - pad thai - thai food \| 131 \| 11_thai_pad_curry_pad thai \|
	\| 12 \| beer - beers - peaks - brewery - craft \| 131 \| 12_beer_beers_peaks_brewery \|
	\| 13 \| breakfast - eggs - pancakes - toast - french toast \| 115 \| 13_breakfast_eggs_pancakes_toast \|
	\| 14 \| pho - vietnamese - spring rolls - spring - broth \| 104 \| 14_pho_vietnamese_spring rolls_spring \|
	\| 15 \| bbq - brisket - ribs - sauce - pork \| 94 \| 15_bbq_brisket_ribs_sauce \|
	\| 16 \| theater - movie - seats - movies - theaters \| 84 \| 16_theater_movie_seats_movies \|
	\| 17 \| food - place - great - lunch - love \| 82 \| 17_food_place_great_lunch \|
	\| 18 \| hair - cut - salon - haircut - barber \| 81 \| 18_hair_cut_salon_haircut \|
	\| 19 \| great - valentine - food - patio - valentine day \| 78 \| 19_great_valentine_food_patio \|
	\| 20 \| service - food - server - servers - food service \| 71 \| 20_service_food_server_servers \|
	\| 21 \| clothes - shoes - store - nordstrom - pair \| 69 \| 21_clothes_shoes_store_nordstrom \|
	\| 22 \| gym - classes - yoga - fitness - workout \| 67 \| 22_gym_classes_yoga_fitness \|
	\| 23 \| phoenix - food - durant - restaurant - good \| 66 \| 23_phoenix_food_durant_restaurant \|
	\| 24 \| italian - pasta - italian food - restaurant - best \| 65 \| 24_italian_pasta_italian food_restaurant \|
	\| 25 \| sandwich - sandwiches - bread - sacks - al \| 64 \| 25_sandwich_sandwiches_bread_sacks \|
	\| 26 \| airport - flight - terminal - sky harbor - harbor \| 64 \| 26_airport_flight_terminal_sky harbor \|
	\| 27 \| yogurt - frozen yogurt - flavors - frozen - toppings \| 64 \| 27_yogurt_frozen yogurt_flavors_frozen \|
	\| 28 \| nails - nail - manicure - pedicure - gel \| 62 \| 28_nails_nail_manicure_pedicure \|
	\| 29 \| car - auto - warranty - repair - new \| 61 \| 29_car_auto_warranty_repair \|
	\| 30 \| trail - hike - park - mountain - view \| 60 \| 30_trail_hike_park_mountain \|
	\| 31 \| dr - doctor - office - care - doctors \| 58 \| 31_dr_doctor_office_care \|
	\| 32 \| ice - ice cream - cream - flavors - custard \| 56 \| 32_ice_ice cream_cream_flavors \|
	\| 33 \| cupcakes - cupcake - cake - frosting - sprinkles \| 54 \| 33_cupcakes_cupcake_cake_frosting \|
	\| 34 \| wine - wines - total wine - daniel - bottle \| 51 \| 34_wine_wines_total wine_daniel \|
	\| 35 \| vegan - vegetarian - meat - mock - green \| 45 \| 35_vegan_vegetarian_meat_mock \|
	\| 36 \| stars - christopher - star - reason - pat \| 45 \| 36_stars_christopher_star_reason \|
	\| 37 \| staff - love place - food - great - friendly \| 45 \| 37_staff_love place_food_great \|
	\| 38 \| stadium - game - spring training - parking - spring \| 44 \| 38_stadium_game_spring training_parking \|
	\| 39 \| sub - subway - subs - jimmy - sandwich \| 44 \| 39_sub_subway_subs_jimmy \|
	\| 40 \| indian - indian food - buffet - india - masala \| 43 \| 40_indian_indian food_buffet_india \|
	\| 41 \| museum - kids - art - exhibits - exhibit \| 40 \| 41_museum_kids_art_exhibits \|
	\| 42 \| donuts - donut - dunkin - bosa - dunkin donuts \| 40 \| 42_donuts_donut_dunkin_bosa \|
	\| 43 \| fez - yelp - yelp event - event - yoli \| 39 \| 43_fez_yelp_yelp event_event \|
	\| 44 \| vet - dog - animals - pet - dogs \| 35 \| 44_vet_dog_animals_pet \|
	\| 45 \| happy hour - happy - hour - great happy - great \| 35 \| 45_happy hour_happy_hour_great happy \|
	\| 46 \| steak - steaks - steakhouse - good steak - sides \| 34 \| 46_steak_steaks_steakhouse_good steak \|
	\| 47 \| mall - stores - malls - shopping - food court \| 33 \| 47_mall_stores_malls_shopping \|
	\| 48 \| phone - store - iphone - camera - customer \| 33 \| 48_phone_store_iphone_camera \|
	\| 49 \| massage - spa - therapist - room - massages \| 33 \| 49_massage_spa_therapist_room \|
	\| 50 \| dog - dogs - hot dog - hot - beef \| 33 \| 50_dog_dogs_hot dog_hot \|
	\| 51 \| dog - pet - dog food - treats - pets \| 32 \| 51_dog_pet_dog food_treats \|
	\| 52 \| closed - location closed - open - closed good - business closed \| 29 \| 52_closed_location closed_open_closed good \|
	\| 53 \| dentist - dr - dental - teeth - office \| 29 \| 53_dentist_dr_dental_teeth \|
	\| 54 \| salad - lunch - sandwich - chicken - dressing \| 29 \| 54_salad_lunch_sandwich_chicken \|
	\| 55 \| greek - greek food - pita - gyro - greek restaurant \| 27 \| 55_greek_greek food_pita_gyro \|
	\| 56 \| waffles - lo - chicken waffles - chicken - lolo \| 27 \| 56_waffles_lo_chicken waffles_chicken \|
	\| 57 \| car - wash - car wash - job - exterior \| 27 \| 57_car_wash_car wash_job \|
	\| 58 \| gelato - angel sweet - angel - italy - flavors \| 27 \| 58_gelato_angel sweet_angel_italy \|
	\| 59 \| wings - wing - love wings - wild wings - buffalo \| 26 \| 59_wings_wing_love wings_wild wings \|
	\| 60 \| tea - boba - teas - drink - milk tea \| 25 \| 60_tea_boba_teas_drink \|
	\| 61 \| food - service - great food - great - awesome food \| 25 \| 61_food_service_great food_great \|
	\| 62 \| bagel - bagels - cream cheese - lox - cream \| 25 \| 62_bagel_bagels_cream cheese_lox \|
	\| 63 \| bruschetta - postino - wine - postinos - bottle \| 24 \| 63_bruschetta_postino_wine_postinos \|
	\| 64 \| review - stars - reviews - hotdog - mold \| 24 \| 64_review_stars_reviews_hotdog \|
	\| 65 \| foods - fresh easy - trader - easy - grocery \| 22 \| 65_foods_fresh easy_trader_easy \|
	\| 66 \| mongolian - mongolian bbq - yc - bowl - bbq \| 22 \| 66_mongolian_mongolian bbq_yc_bowl \|
	\| 67 \| service - food - time - horrible - ordered \| 22 \| 67_service_food_time_horrible \|
	\| 68 \| course - holes - courses - played - tee \| 21 \| 68_course_holes_courses_played \|
	\| 69 \| dog - dogs - park - dog park - active \| 21 \| 69_dog_dogs_park_dog park \|
	\| 70 \| books - book - library - bookstore - used books \| 21 \| 70_books_book_library_bookstore \|
	\| 71 \| pita - pita jungle - jungle - hummus - lentil \| 20 \| 71_pita_pita jungle_jungle_hummus \|
	\| 72 \| pasta - spaghetti - sauce - italian - bread \| 20 \| 72_pasta_spaghetti_sauce_italian \|
	\| 73 \| store - office max - prices - max - office \| 20 \| 73_store_office max_prices_max \|
	\| 74 \| expensive - good price - food - price - good food \| 19 \| 74_expensive_good price_food_price \|
	\| 75 \| thrift - store - goodwill - thrift store - vintage \| 19 \| 75_thrift_store_goodwill_thrift store \|
	\| 76 \| safeway - store - grocery - shopping - winco \| 19 \| 76_safeway_store_grocery_shopping \|
	\| 77 \| beer - bar - asked - minutes - trout \| 18 \| 77_beer_bar_asked_minutes \|
	\| 78 \| japanese - tokyo - japanese food - knife - knives \| 18 \| 78_japanese_tokyo_japanese food_knife \|
	\| 79 \| irish - pub - irish pub - fish chips - guinness \| 16 \| 79_irish_pub_irish pub_fish chips \|
	\| 80 \| works meh - friendly awesome - ing great - awesome intense - job super \| 16 \| 80_works meh_friendly awesome_ing great_awesome intense \|
	\| 81 \| zia - record - cd - stinkweeds - music \| 15 \| 81_zia_record_cd_stinkweeds \|
	\| 82 \| tires - tire - discount tire - discount - new tires \| 14 \| 82_tires_tire_discount tire_discount \|
	\| 83 \| cheesesteak - wiz - cheesesteaks - forefathers - philly \| 14 \| 83_cheesesteak_wiz_cheesesteaks_forefathers \|
	\| 84 \| korean - korean food - kimchi - bbq - dishes \| 14 \| 84_korean_korean food_kimchi_bbq \|
	\| 85 \| buffet - buffets - sushi - hong - hong kong \| 13 \| 85_buffet_buffets_sushi_hong \|
	\| 86 \| gyro - tzatziki - pita - gyros - meat \| 13 \| 86_gyro_tzatziki_pita_gyros \|
	\| 87 \| classes - campus - school - teacher - students \| 13 \| 87_classes_campus_school_teacher \|
	\| 88 \| romantic - love love - whinings excellent - whinings - live amazing \| 13 \| 88_romantic_love love_whinings excellent_whinings \|
	\| 89 \| patio - service - excellent service - excellent - great service \| 12 \| 89_patio_service_excellent service_excellent \|
	\| 90 \| staff - clean staff - clean - selection awesome - friendly \| 12 \| 90_staff_clean staff_clean_selection awesome \|
	\| 91 \| lux - coffee - espresso - love space - surfing \| 12 \| 91_lux_coffee_espresso_love space \|
	\| 92 \| wine - bottle - glass - bar - maybe \| 12 \| 92_wine_bottle_glass_bar \|
	\| 93 \| sushi - roll - ra - sushi bar - seated \| 12 \| 93_sushi_roll_ra_sushi bar \|
	\| 94 \| german - schnitzel - murphy - german food - haus \| 12 \| 94_german_schnitzel_murphy_german food \|
	\| 95 \| ethiopian - lalibela - injera - watt - lentils \| 11 \| 95_ethiopian_lalibela_injera_watt \|
	\| 96 \| store - items - michaels - susan - employee \| 11 \| 96_store_items_michaels_susan \|

	</details>

	## Training hyperparameters

	* calculate_probabilities: True
	* 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: True
	* zeroshot_min_similarity: 0.7
	* zeroshot_topic_list: None

	## Framework versions

	* Numpy: 1.25.2
	* HDBSCAN: 0.8.36
	* UMAP: 0.5.6
	* Pandas: 2.0.3
	* Scikit-Learn: 1.2.2
	* Sentence-transformers: 3.0.0
	* Transformers: 4.41.1
	* Numba: 0.58.1
	* Plotly: 5.15.0
	* Python: 3.10.12


	---
	tags:
	- bertopic
	library_name: bertopic
	pipeline_tag: text-classification
	---

	# yelpreview_base

	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("Ayomidedeji/yelpreview_base")

	topic_model.get_topic_info()
	```

	## Topic overview

	* Number of topics: 98
	* Number of training documents: 10000

	<details>
	<summary>Click here for an overview of all topics.</summary>

	\| Topic ID \| Topic Keywords \| Topic Frequency \| Label \|
	\|----------\|----------------\|-----------------\|-------\|
	\| -1 \| food - good - place - great - like \| 10 \| -1_food_good_place_great \|
	\| 0 \| mexican - tacos - salsa - burrito - food \| 3827 \| 0_mexican_tacos_salsa_burrito \|
	\| 1 \| pizza - crust - pizzas - good - wait \| 705 \| 1_pizza_crust_pizzas_good \|
	\| 2 \| bar - music - drinks - night - place \| 393 \| 2_bar_music_drinks_night \|
	\| 3 \| burger - fries - burgers - good - like \| 288 \| 3_burger_fries_burgers_good \|
	\| 4 \| ordered - just - bread - good - chicken \| 275 \| 4_ordered_just_bread_good \|
	\| 5 \| sushi - roll - rolls - happy hour - happy \| 261 \| 5_sushi_roll_rolls_happy hour \|
	\| 6 \| scottsdale - place - great - bar - food \| 191 \| 6_scottsdale_place_great_bar \|
	\| 7 \| coffee - starbucks - coffee shop - shop - espresso \| 190 \| 7_coffee_starbucks_coffee shop_shop \|
	\| 8 \| hotel - pool - room - stay - resort \| 186 \| 8_hotel_pool_room_stay \|
	\| 9 \| minutes - table - server - asked - came \| 183 \| 9_minutes_table_server_asked \|
	\| 10 \| chinese - chinese food - food - asian - china \| 145 \| 10_chinese_chinese food_food_asian \|
	\| 11 \| thai - pad - curry - pad thai - thai food \| 131 \| 11_thai_pad_curry_pad thai \|
	\| 12 \| beer - beers - peaks - brewery - craft \| 131 \| 12_beer_beers_peaks_brewery \|
	\| 13 \| breakfast - eggs - pancakes - toast - french toast \| 115 \| 13_breakfast_eggs_pancakes_toast \|
	\| 14 \| pho - vietnamese - spring rolls - spring - broth \| 104 \| 14_pho_vietnamese_spring rolls_spring \|
	\| 15 \| bbq - brisket - ribs - sauce - pork \| 94 \| 15_bbq_brisket_ribs_sauce \|
	\| 16 \| theater - movie - seats - movies - theaters \| 84 \| 16_theater_movie_seats_movies \|
	\| 17 \| food - place - great - lunch - love \| 82 \| 17_food_place_great_lunch \|
	\| 18 \| hair - cut - salon - haircut - barber \| 81 \| 18_hair_cut_salon_haircut \|
	\| 19 \| great - valentine - food - patio - valentine day \| 78 \| 19_great_valentine_food_patio \|
	\| 20 \| service - food - server - servers - food service \| 71 \| 20_service_food_server_servers \|
	\| 21 \| clothes - shoes - store - nordstrom - pair \| 69 \| 21_clothes_shoes_store_nordstrom \|
	\| 22 \| gym - classes - yoga - fitness - workout \| 67 \| 22_gym_classes_yoga_fitness \|
	\| 23 \| phoenix - food - durant - restaurant - good \| 66 \| 23_phoenix_food_durant_restaurant \|
	\| 24 \| italian - pasta - italian food - restaurant - best \| 65 \| 24_italian_pasta_italian food_restaurant \|
	\| 25 \| sandwich - sandwiches - bread - sacks - al \| 64 \| 25_sandwich_sandwiches_bread_sacks \|
	\| 26 \| airport - flight - terminal - sky harbor - harbor \| 64 \| 26_airport_flight_terminal_sky harbor \|
	\| 27 \| yogurt - frozen yogurt - flavors - frozen - toppings \| 64 \| 27_yogurt_frozen yogurt_flavors_frozen \|
	\| 28 \| nails - nail - manicure - pedicure - gel \| 62 \| 28_nails_nail_manicure_pedicure \|
	\| 29 \| car - auto - warranty - repair - new \| 61 \| 29_car_auto_warranty_repair \|
	\| 30 \| trail - hike - park - mountain - view \| 60 \| 30_trail_hike_park_mountain \|
	\| 31 \| dr - doctor - office - care - doctors \| 58 \| 31_dr_doctor_office_care \|
	\| 32 \| ice - ice cream - cream - flavors - custard \| 56 \| 32_ice_ice cream_cream_flavors \|
	\| 33 \| cupcakes - cupcake - cake - frosting - sprinkles \| 54 \| 33_cupcakes_cupcake_cake_frosting \|
	\| 34 \| wine - wines - total wine - daniel - bottle \| 51 \| 34_wine_wines_total wine_daniel \|
	\| 35 \| vegan - vegetarian - meat - mock - green \| 45 \| 35_vegan_vegetarian_meat_mock \|
	\| 36 \| stars - christopher - star - reason - pat \| 45 \| 36_stars_christopher_star_reason \|
	\| 37 \| staff - love place - food - great - friendly \| 45 \| 37_staff_love place_food_great \|
	\| 38 \| stadium - game - spring training - parking - spring \| 44 \| 38_stadium_game_spring training_parking \|
	\| 39 \| sub - subway - subs - jimmy - sandwich \| 44 \| 39_sub_subway_subs_jimmy \|
	\| 40 \| indian - indian food - buffet - india - masala \| 43 \| 40_indian_indian food_buffet_india \|
	\| 41 \| museum - kids - art - exhibits - exhibit \| 40 \| 41_museum_kids_art_exhibits \|
	\| 42 \| donuts - donut - dunkin - bosa - dunkin donuts \| 40 \| 42_donuts_donut_dunkin_bosa \|
	\| 43 \| fez - yelp - yelp event - event - yoli \| 39 \| 43_fez_yelp_yelp event_event \|
	\| 44 \| vet - dog - animals - pet - dogs \| 35 \| 44_vet_dog_animals_pet \|
	\| 45 \| happy hour - happy - hour - great happy - great \| 35 \| 45_happy hour_happy_hour_great happy \|
	\| 46 \| steak - steaks - steakhouse - good steak - sides \| 34 \| 46_steak_steaks_steakhouse_good steak \|
	\| 47 \| mall - stores - malls - shopping - food court \| 33 \| 47_mall_stores_malls_shopping \|
	\| 48 \| phone - store - iphone - camera - customer \| 33 \| 48_phone_store_iphone_camera \|
	\| 49 \| massage - spa - therapist - room - massages \| 33 \| 49_massage_spa_therapist_room \|
	\| 50 \| dog - dogs - hot dog - hot - beef \| 33 \| 50_dog_dogs_hot dog_hot \|
	\| 51 \| dog - pet - dog food - treats - pets \| 32 \| 51_dog_pet_dog food_treats \|
	\| 52 \| closed - location closed - open - closed good - business closed \| 29 \| 52_closed_location closed_open_closed good \|
	\| 53 \| dentist - dr - dental - teeth - office \| 29 \| 53_dentist_dr_dental_teeth \|
	\| 54 \| salad - lunch - sandwich - chicken - dressing \| 29 \| 54_salad_lunch_sandwich_chicken \|
	\| 55 \| greek - greek food - pita - gyro - greek restaurant \| 27 \| 55_greek_greek food_pita_gyro \|
	\| 56 \| waffles - lo - chicken waffles - chicken - lolo \| 27 \| 56_waffles_lo_chicken waffles_chicken \|
	\| 57 \| car - wash - car wash - job - exterior \| 27 \| 57_car_wash_car wash_job \|
	\| 58 \| gelato - angel sweet - angel - italy - flavors \| 27 \| 58_gelato_angel sweet_angel_italy \|
	\| 59 \| wings - wing - love wings - wild wings - buffalo \| 26 \| 59_wings_wing_love wings_wild wings \|
	\| 60 \| tea - boba - teas - drink - milk tea \| 25 \| 60_tea_boba_teas_drink \|
	\| 61 \| food - service - great food - great - awesome food \| 25 \| 61_food_service_great food_great \|
	\| 62 \| bagel - bagels - cream cheese - lox - cream \| 25 \| 62_bagel_bagels_cream cheese_lox \|
	\| 63 \| bruschetta - postino - wine - postinos - bottle \| 24 \| 63_bruschetta_postino_wine_postinos \|
	\| 64 \| review - stars - reviews - hotdog - mold \| 24 \| 64_review_stars_reviews_hotdog \|
	\| 65 \| foods - fresh easy - trader - easy - grocery \| 22 \| 65_foods_fresh easy_trader_easy \|
	\| 66 \| mongolian - mongolian bbq - yc - bowl - bbq \| 22 \| 66_mongolian_mongolian bbq_yc_bowl \|
	\| 67 \| service - food - time - horrible - ordered \| 22 \| 67_service_food_time_horrible \|
	\| 68 \| course - holes - courses - played - tee \| 21 \| 68_course_holes_courses_played \|
	\| 69 \| dog - dogs - park - dog park - active \| 21 \| 69_dog_dogs_park_dog park \|
	\| 70 \| books - book - library - bookstore - used books \| 21 \| 70_books_book_library_bookstore \|
	\| 71 \| pita - pita jungle - jungle - hummus - lentil \| 20 \| 71_pita_pita jungle_jungle_hummus \|
	\| 72 \| pasta - spaghetti - sauce - italian - bread \| 20 \| 72_pasta_spaghetti_sauce_italian \|
	\| 73 \| store - office max - prices - max - office \| 20 \| 73_store_office max_prices_max \|
	\| 74 \| expensive - good price - food - price - good food \| 19 \| 74_expensive_good price_food_price \|
	\| 75 \| thrift - store - goodwill - thrift store - vintage \| 19 \| 75_thrift_store_goodwill_thrift store \|
	\| 76 \| safeway - store - grocery - shopping - winco \| 19 \| 76_safeway_store_grocery_shopping \|
	\| 77 \| beer - bar - asked - minutes - trout \| 18 \| 77_beer_bar_asked_minutes \|
	\| 78 \| japanese - tokyo - japanese food - knife - knives \| 18 \| 78_japanese_tokyo_japanese food_knife \|
	\| 79 \| irish - pub - irish pub - fish chips - guinness \| 16 \| 79_irish_pub_irish pub_fish chips \|
	\| 80 \| works meh - friendly awesome - ing great - awesome intense - job super \| 16 \| 80_works meh_friendly awesome_ing great_awesome intense \|
	\| 81 \| zia - record - cd - stinkweeds - music \| 15 \| 81_zia_record_cd_stinkweeds \|
	\| 82 \| tires - tire - discount tire - discount - new tires \| 14 \| 82_tires_tire_discount tire_discount \|
	\| 83 \| cheesesteak - wiz - cheesesteaks - forefathers - philly \| 14 \| 83_cheesesteak_wiz_cheesesteaks_forefathers \|
	\| 84 \| korean - korean food - kimchi - bbq - dishes \| 14 \| 84_korean_korean food_kimchi_bbq \|
	\| 85 \| buffet - buffets - sushi - hong - hong kong \| 13 \| 85_buffet_buffets_sushi_hong \|
	\| 86 \| gyro - tzatziki - pita - gyros - meat \| 13 \| 86_gyro_tzatziki_pita_gyros \|
	\| 87 \| classes - campus - school - teacher - students \| 13 \| 87_classes_campus_school_teacher \|
	\| 88 \| romantic - love love - whinings excellent - whinings - live amazing \| 13 \| 88_romantic_love love_whinings excellent_whinings \|
	\| 89 \| patio - service - excellent service - excellent - great service \| 12 \| 89_patio_service_excellent service_excellent \|
	\| 90 \| staff - clean staff - clean - selection awesome - friendly \| 12 \| 90_staff_clean staff_clean_selection awesome \|
	\| 91 \| lux - coffee - espresso - love space - surfing \| 12 \| 91_lux_coffee_espresso_love space \|
	\| 92 \| wine - bottle - glass - bar - maybe \| 12 \| 92_wine_bottle_glass_bar \|
	\| 93 \| sushi - roll - ra - sushi bar - seated \| 12 \| 93_sushi_roll_ra_sushi bar \|
	\| 94 \| german - schnitzel - murphy - german food - haus \| 12 \| 94_german_schnitzel_murphy_german food \|
	\| 95 \| ethiopian - lalibela - injera - watt - lentils \| 11 \| 95_ethiopian_lalibela_injera_watt \|
	\| 96 \| store - items - michaels - susan - employee \| 11 \| 96_store_items_michaels_susan \|

	</details>

	## Training hyperparameters

	* calculate_probabilities: True
	* 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: True
	* zeroshot_min_similarity: 0.7
	* zeroshot_topic_list: None

	## Framework versions

	* Numpy: 1.25.2
	* HDBSCAN: 0.8.36
	* UMAP: 0.5.6
	* Pandas: 2.0.3
	* Scikit-Learn: 1.2.2
	* Sentence-transformers: 3.0.0
	* Transformers: 4.41.1
	* Numba: 0.58.1
	* Plotly: 5.15.0
	* Python: 3.10.12