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This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set.

This is a sentence-transformers model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or ...

11 апр. 2022 г. · T5, bart are all good models, the general class is seq2seq. There are plenty here. My concern would be finding a suitable set to train ...

Keyword Extraction from Short Texts with T5 Our vlT5 model is a keyword generation model based on encoder-decoder architecture using Transformer blocks ...

5 окт. 2023 г. · With KeyLLM you are able to use Large Language Models to help create better keywords. We can choose to extract keywords from the text itself or ...

This model extracts tech terms, tools, company names from texts so they can easily be aggregated. It is trained to extract tech terms, tools, languages, ...

KeyBERT is a minimal and easy-to-use keyword extraction technique that leverages BERT embeddings to create keywords and keyphrases that are most similar to a ... MIT License · README.md · Releases 11

Model Card for Model ID. This model is meant to extract keywords from text. Model type: text-classification; Language(s) (NLP): English; License: cc ...

It is an easy-to-use Python package for keyphrase extraction with BERT language models. Shortly explained, KeyBERT works by first creating BERT embeddings ...