Instructions to use AIDA-UPM/MARTINI_enrich_BERTopic_ConPy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- BERTopic
How to use AIDA-UPM/MARTINI_enrich_BERTopic_ConPy with BERTopic:
from bertopic import BERTopic model = BERTopic.load("AIDA-UPM/MARTINI_enrich_BERTopic_ConPy") - Notebooks
- Google Colab
- Kaggle
Download ctfidf_config.json from AIDA-UPM/MARTINI_enrich_BERTopic_ConPy: direct link, hf CLI and curl.
- Browser
- Download file 256 kB
-
https://huggingface.co/AIDA-UPM/MARTINI_enrich_BERTopic_ConPy/resolve/main/ctfidf_config.json
- Command line
-
hf download hf://AIDA-UPM/MARTINI_enrich_BERTopic_ConPy/ctfidf_config.json
-
curl -L -o ctfidf_config.json https://huggingface.co/AIDA-UPM/MARTINI_enrich_BERTopic_ConPy/resolve/main/ctfidf_config.json
256 kB
| { | |
| "ctfidf_model": { | |
| "bm25_weighting": false, | |
| "reduce_frequent_words": true | |
| }, | |
| "vectorizer_model": { | |
| "params": { | |
| "analyzer": "word", | |
| "binary": false, | |
| "decode_error": "strict", | |
| "encoding": "utf-8", | |
| "input": "content", | |
| "lowercase": true, | |
| "max_df": 0.8, | |
| "max_features": null, | |
| "min_df": 1, | |
| "ngram_range": [ | |
| 1, | |
| 1 | |
| ], | |
| "stop_words": [ | |
| "i", | |
| "me", | |
| "my", | |
| "myself", | |
| "we", | |
| "our", | |
| "ours", | |
| "ourselves", | |
| "you", | |
| "you're", | |
| "you've", | |
| "you'll", | |
| "you'd", | |
| "your", | |
| "yours", | |
| "yourself", | |
| "yourselves", | |
| "he", | |
| "him", | |
| "his", | |
| "himself", | |
| "she", | |
| "she's", | |
| "her", | |
| "hers", | |
| "herself", | |
| "it", | |
| "it's", | |
| "its", | |
| "itself", | |
| "they", | |
| "them", | |
| "their", | |
| "theirs", | |
| "themselves", | |
| "what", | |
| "which", | |
| "who", | |
| "whom", | |
| "this", | |
| "that", | |
| "that'll", | |
| "these", | |
| "those", | |
| "am", | |
| "is", | |
| "are", | |
| "was", | |
| "were", | |
| "be", | |
| "been", | |
| "being", | |
| "have", | |
| "has", | |
| "had", | |
| "having", | |
| "do", | |
| "does", | |
| "did", | |
| "doing", | |
| "a", | |
| "an", | |
| "the", | |
| "and", | |
| "but", | |
| "if", | |
| "or", | |
| "because", | |
| "as", | |
| "until", | |
| "while", | |
| "of", | |
| "at", | |
| "by", | |
| "for", | |
| "with", | |
| "about", | |
| "against", | |
| "between", | |
| "into", | |
| "through", | |
| "during", | |
| "before", | |
| "after", | |
| "above", | |
| "below", | |
| "to", | |
| "from", | |
| "up", | |
| "down", | |
| "in", | |
| "out", | |
| "on", | |
| "off", | |
| "over", | |
| "under", | |
| "again", | |
| "further", | |
| "then", | |
| "once", | |
| "here", | |
| "there", | |
| "when", | |
| "where", | |
| "why", | |
| "how", | |
| "all", | |
| "any", | |
| "both", | |
| "each", | |
| "few", | |
| "more", | |
| "most", | |
| "other", | |
| "some", | |
| "such", | |
| "no", | |
| "nor", | |
| "not", | |
| "only", | |
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| "same", | |
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| "too", | |
| "very", | |
| "s", | |
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| "isn", | |
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| "ma", | |
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| "mustn't", | |
| "needn", | |
| "needn't", | |
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| "shouldn't", | |
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| "wasn't", | |
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| "weren't", | |
| "won", | |
| "won't", | |
| "wouldn", | |
| "wouldn't", | |
| "ConPy" | |
| ], | |
| "strip_accents": "unicode", | |
| "token_pattern": "(?u)\\b\\w\\w+\\b", | |
| "vocabulary": null | |
| }, | |
| "vocab": { | |
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| "occult": 6777, | |
| "conspiracy": 2265, | |
| "1998": 96, | |
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