|
|
| ---
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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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|
|
| # BERTopic
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|
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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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|
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| ## Usage
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|
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| To use this model, please install BERTopic:
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|
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| ```
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| pip install -U bertopic
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| ```
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|
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| You can use the model as follows:
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|
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| ```python
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| from bertopic import BERTopic
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| topic_model = BERTopic.load("zsozsi12/BERTopic")
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|
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| topic_model.get_topic_info()
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| ```
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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: 1152
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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 | az - is - de - nem - nagyon | 12 | -1_az_is_de_nem |
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| | 0 | az - nem - nekem - is - de | 394 | 0_az_nem_nekem_is |
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| | 1 | netflix - az - hogy - egy - nem | 147 | 1_netflix_az_hogy_egy |
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| | 2 | the - you - stranger - things - breaking | 115 | 2_the_you_stranger_things |
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| | 3 | hogy - az - is - nem - egy | 105 | 3_hogy_az_is_nem |
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| | 4 | film - az - de - nem - egy | 61 | 4_film_az_de_nem |
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| | 5 | disney - spotify - youtube - netflix - hbo | 61 | 5_disney_spotify_youtube_netflix |
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| | 6 | hogy - egy - nem - vagy - de | 60 | 6_hogy_egy_nem_vagy |
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| | 7 | hogy - nem - netflix - is - az | 55 | 7_hogy_nem_netflix_is |
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| | 8 | valaki - nem - mg - meg - sem | 41 | 8_valaki_nem_mg_meg |
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| | 9 | teljesen - nem - teljes - az - ha | 36 | 9_teljesen_nem_teljes_az |
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| | 10 | nagyon - szerintem - volt - sorozat - annyira | 28 | 10_nagyon_szerintem_volt_sorozat |
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| | 11 | mint - olyan - normlis - knyv - forint | 25 | 11_mint_olyan_normlis_knyv |
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| | 12 | tv - van - apple - nem - fhd | 12 | 12_tv_van_apple_nem |
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|
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| </details>
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|
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| ## Training hyperparameters
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|
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| * calculate_probabilities: False
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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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| * zeroshot_min_similarity: 0.7
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| * zeroshot_topic_list: None
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|
|
| ## Framework versions
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|
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| * Numpy: 1.26.4
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| * HDBSCAN: 0.8.40
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| * UMAP: 0.5.9.post2
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| * Pandas: 2.2.3
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| * Scikit-Learn: 1.7.1
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| * Sentence-transformers: 5.1.0
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| * Transformers: 4.56.1
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| * Numba: 0.61.2
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| * Plotly: 5.22.0
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| * Python: 3.12.2
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| |
