# Zero shot learning classification

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**Category:** Beginners\
**Created:** [December 8, 2020, 8:41pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fzero-shot-learning-classification%2F2707 "2020-12-08T20:41:34Z")\
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**Author:** ![MoritzLaurer](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/moritzlaurer/32/18932_2.png) [@MoritzLaurer](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2FMoritzLaurer)%5C
**Post date:** [December 8, 2020, 9:15pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fzero-shot-learning-classification%2F2707%2F2 "2020-12-08T21:15:40Z")

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When you select the tag zero-shot-classification in the model hub ([see here](https://huggingface.co/models?filter=zero-shot-classification)) you can see all the models for the task. The default in the pipeline is `facebook/bart-large-mnli` (see [source code here](https://github.com/huggingface/transformers/blob/master/src/transformers/pipelines.py#L2790))

Hugging Face’s zero-shot classification is always based on models pre-trained on Natural Language Inference datasets (like mnli). So under the hood, it’s actually doing an NLI classification, it’s just abstracting that part away for you ([see details and further links here](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fnew-pipeline-for-zero-shot-text-classification%2F681))

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