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  A Siamese network model trained for zero-shot and few-shot text classification.
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  The base model is [xlm-roberta-base](https://huggingface.co/xlm-roberta-base).
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- It was trained on [SNLI](https://nlp.stanford.edu/projects/snli/) and [MNLI](https://cims.nyu.edu/~sbowman/multinli/), [ANLI](https://github.com/facebookresearch/anli) and [XNLI](https://github.com/facebookresearch/XNLI).
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  This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space.
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  A Siamese network model trained for zero-shot and few-shot text classification.
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  The base model is [xlm-roberta-base](https://huggingface.co/xlm-roberta-base).
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+ It was trained on [SNLI](https://nlp.stanford.edu/projects/snli/), [MNLI](https://cims.nyu.edu/~sbowman/multinli/), [ANLI](https://github.com/facebookresearch/anli) and [XNLI](https://github.com/facebookresearch/XNLI).
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  This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space.
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