Helsinki-NLP/HBMP
Sentence Embeddings in NLI with Iterative Refinement Encoders
This project helps natural language processing researchers evaluate how well different methods capture the meaning of sentences. It takes a collection of text sentences as input and produces numerical representations (embeddings) that encode their meaning. This allows researchers to compare the effectiveness of various models in understanding language for tasks like determining if one sentence logically follows another.
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Use this if you are an NLP researcher working on sentence embeddings and need to benchmark their performance on natural language inference tasks.
Not ideal if you are a practitioner looking for a ready-to-use API for general text analysis or a non-technical user.
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80
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16
Language
Python
License
MIT
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Last pushed
Nov 22, 2022
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