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  base model: [Alibaba-NLP/gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5)
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  <!--- Describe your model here -->
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- We finetuned the model to help compute (approximate) soft scores for textual entailment to help find the option that entails the response from a model who's response is not conditioned on the options.
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  ## Usage (Sentence-Transformers)
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  This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
 
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  base model: [Alibaba-NLP/gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5)
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  <!--- Describe your model here -->
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+ We finetuned the model to help compute (approximate) soft scores for textual entailment to help find the option that entails the response from a model whose response is not conditioned on the options.
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  ## Usage (Sentence-Transformers)
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  This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.