Add BERTopic model
Browse files- README.md +82 -0
- config.json +15 -0
- topic_embeddings.safetensors +3 -0
- topics.json +2250 -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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# cnn_dailymail_55555_3000_1500_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/cnn_dailymail_55555_3000_1500_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: 15
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* Number of training documents: 1500
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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 | season - league - player - club - game | 13 | -1_season_league_player_club |
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| 0 | said - one - people - year - also | 121 | 0_said_one_people_year |
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| 1 | madrid - real - barcelona - league - atletico | 1080 | 1_madrid_real_barcelona_league |
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| 2 | sterling - liverpool - league - club - season | 41 | 2_sterling_liverpool_league_club |
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| 3 | try - game - minute - wolves - back | 35 | 3_try_game_minute_wolves |
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| 4 | chelsea - league - hazard - premier - mourinho | 27 | 4_chelsea_league_hazard_premier |
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| 5 | lady - race - djokovic - victory - oxford | 24 | 5_lady_race_djokovic_victory |
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| 6 | england - cricket - test - wicket - pietersen | 24 | 6_england_cricket_test_wicket |
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| 7 | villa - sherwood - liverpool - cup - fa | 23 | 7_villa_sherwood_liverpool_cup |
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| 8 | united - manchester - van - gaal - carrick | 23 | 8_united_manchester_van_gaal |
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| 9 | fight - mayweather - pacquiao - ticket - manny | 23 | 9_fight_mayweather_pacquiao_ticket |
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| 10 | bayern - guardiola - munich - porto - ribery | 21 | 10_bayern_guardiola_munich_porto |
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| 11 | masters - woods - augusta - mcilroy - shot | 16 | 11_masters_woods_augusta_mcilroy |
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| 12 | rangers - scottish - game - celtic - hearts | 15 | 12_rangers_scottish_game_celtic |
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| 13 | race - hamilton - rosberg - car - ferrari | 14 | 13_race_hamilton_rosberg_car |
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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: 0.56.4
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* Plotly: 5.13.1
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* Python: 3.10.6
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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 sha256:9e1d803835c60562cd12f08538b79a20fa86d4de4956312d6a796db44b260efc
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size 23128
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topics.json
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