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README.md
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@@ -14,17 +14,11 @@ BERTopic is a flexible and modular topic modeling framework that allows for the
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This pre-trained model demonstrates the use of several representation models that can be used within BERTopic. This model was trained on ~30000 ArXiv abstracts with the following topic representation methods (`bertopic.representation`):
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* POS
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* `PartOfSpeech("en_core_web_lg")`
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* KeyBERTInspired
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* `[KeyBERTInspired(), MaximalMarginalRelevance(diversity=0.3)]`
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* OpenAI_Label
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* `OpenAI(model="gpt-3.5-turbo", exponential_backoff=True, chat=True, diversity=0.1)`
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* OpenAI_Summary
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* `[KeyBERTInspired(), summarization_model]`
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An example of the default c-TF-IDF representations:
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This pre-trained model demonstrates the use of several representation models that can be used within BERTopic. This model was trained on ~30000 ArXiv abstracts with the following topic representation methods (`bertopic.representation`):
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* POS
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* KeyBERTInspired
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* MaximalMarginalRelevance
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* KeyBERT + MaximalMarginalRelevance
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* ChatGPT labels
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* ChatGPT summaries
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An example of the default c-TF-IDF representations:
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