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wongzien2000/
model_wolf

Name: model_wolf
Rating: 2.5 (6 reviews)

bertopic

text-classification

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model_wolf

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:

python

from bertopic import BERTopic
topic_model = BERTopic.load("wongzien2000/model_wolf")

topic_model.get_topic_info()

Topic overview

Number of topics: 19
Number of training documents: 2933

Click here for an overview of all topics.

Topic ID	Topic Keywords	Topic Frequency	Label
-1	split - great - creatine - best - exercise	37	-1_split_great_creatine_best
0	cable - just - exercise - exercises - lateral	468	0_cable_just_exercise_exercises
1	mike - dr - dr mike - darth - sith	1267	1_mike_dr_dr mike_darth
2	sets - protein - week - muscle - volume	166	2_sets_protein_week_muscle
3	deadlift - deadlifts - strength - hypertrophy - legs	107	3_deadlift_deadlifts_strength_hypertrophy
4	tier - list - accent - tier list - pencil	95	4_tier_list_accent_tier list
5	pistol - squats - pistol squats - squat - reverse	80	5_pistol_squats_pistol squats_squat
6	tier - deadlift tier - deadlift - sticky ricky - ricky	79	6_tier_deadlift tier_deadlift_sticky ricky
7	uncles - stamps - time stamps - comment - timestamps	77	7_uncles_stamps_time stamps_comment
8	sound - audio - ai - milo - sound effects	75	8_sound_audio_ai_milo
9	curl - incline - curls - preacher - preacher curl	74	9_curl_incline_curls_preacher
10	milo - dr milo - hear - ending - miew	73	10_milo_dr milo_hear_ending
11	leg - leg extension - extension - quads - quad	54	11_leg_leg extension_extension_quads
12	calf - calf raise - seated calf - seated - calves	54	12_calf_calf raise_seated calf_seated
13	partials - lengthened partials - lengthened - song - grandma	50	13_partials_lengthened partials_lengthened_song
14	wolf - dr wolf - meadows - meadows row - dr	46	14_wolf_dr wolf_meadows_meadows row
15	squats - squat - hack - sissy - sissy squats	45	15_squats_squat_hack_sissy
16	app - myoadapt - december - waiting - coming	43	16_app_myoadapt_december_waiting
17	mike - interviewing mike - bomb - interviewing - love mike	43	17_mike_interviewing mike_bomb_interviewing

Training hyperparameters

calculate_probabilities: True
language: None
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: 2.0.2
HDBSCAN: 0.8.40
UMAP: 0.5.7
Pandas: 2.2.2
Scikit-Learn: 1.6.1
Sentence-transformers: 3.4.1
Transformers: 4.50.2
Numba: 0.60.0
Plotly: 5.24.1
Python: 3.11.11