|
|
| --- |
| tags: |
| - bertopic |
| library_name: bertopic |
| pipeline_tag: text-classification |
| --- |
| |
| # model_wolf |
| |
| 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("wongzien2000/model_wolf") |
| |
| topic_model.get_topic_info() |
| ``` |
| |
| ## Topic overview |
| |
| * Number of topics: 19 |
| * Number of training documents: 2933 |
| |
| <details> |
| <summary>Click here for an overview of all topics.</summary> |
| |
| | 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 | |
| |
| </details> |
| |
| ## 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 |
| |
