Add BERTopic model
Browse files- README.md +81 -0
- config.json +15 -0
- topic_embeddings.safetensors +3 -0
- topics.json +0 -0
README.md
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---
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tags:
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- bertopic
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library_name: bertopic
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pipeline_tag: text-classification
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---
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# xsum_108_5000000_2500000_test
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This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
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BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
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## Usage
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To use this model, please install BERTopic:
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```
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pip install -U bertopic
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```
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You can use the model as follows:
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```python
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from bertopic import BERTopic
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topic_model = BERTopic.load("KingKazma/xsum_108_5000000_2500000_test")
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topic_model.get_topic_info()
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```
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## Topic overview
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* Number of topics: 14
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* Number of training documents: 11334
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<details>
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<summary>Click here for an overview of all topics.</summary>
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| Topic ID | Topic Keywords | Topic Frequency | Label |
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|----------|----------------|-----------------|-------|
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| -1 | said - win - first - one - time | 13 | -1_said_win_first_one |
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| 0 | said - mr - would - people - also | 1003 | 0_said_mr_would_people |
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| 1 | win - game - league - goal - right | 7868 | 1_win_game_league_goal |
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| 2 | race - olympic - sport - gold - team | 1707 | 2_race_olympic_sport_gold |
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| 3 | england - cricket - wicket - test - captain | 225 | 3_england_cricket_wicket_test |
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| 4 | race - hamilton - mercedes - f1 - lap | 192 | 4_race_hamilton_mercedes_f1 |
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| 5 | match - murray - konta - seed - set | 62 | 5_match_murray_konta_seed |
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| 6 | round - birdie - shot - par - bogey | 59 | 6_round_birdie_shot_par |
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| 7 | fight - boxing - champion - ali - title | 49 | 7_fight_boxing_champion_ali |
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| 8 | yn - ar - ei - yr - wedi | 48 | 8_yn_ar_ei_yr |
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| 9 | unsupported - updated - playback - media - device | 33 | 9_unsupported_updated_playback_media |
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| 10 | world - champion - osullivan - event - snooker | 29 | 10_world_champion_osullivan_event |
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| 11 | fifa - blatter - football - platini - fifas | 25 | 11_fifa_blatter_football_platini |
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| 12 | ebola - sierra - leone - outbreak - people | 21 | 12_ebola_sierra_leone_outbreak |
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</details>
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## Training hyperparameters
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* calculate_probabilities: True
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* language: english
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* low_memory: False
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* min_topic_size: 10
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* n_gram_range: (1, 1)
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* nr_topics: None
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* seed_topic_list: None
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* top_n_words: 10
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* verbose: False
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## Framework versions
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* Numpy: 1.22.4
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* HDBSCAN: 0.8.33
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* UMAP: 0.5.3
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* Pandas: 1.5.3
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* Scikit-Learn: 1.2.2
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* Sentence-transformers: 2.2.2
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* Transformers: 4.31.0
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* Numba: 0.57.1
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* Plotly: 5.13.1
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* Python: 3.10.12
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config.json
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{
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"calculate_probabilities": true,
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"language": "english",
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"low_memory": false,
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"min_topic_size": 10,
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"n_gram_range": [
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1,
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1
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],
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"nr_topics": null,
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"seed_topic_list": null,
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"top_n_words": 10,
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"verbose": false,
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"embedding_model": "sentence-transformers/all-MiniLM-L6-v2"
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}
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topic_embeddings.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7066515e4043182de69ef1cd986471c942834086630432a3406944084e4acf91
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size 21592
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topics.json
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