Use HF papers (#38184)
* Use hf papers * Hugging Face papers * doi to hf papers * style
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@@ -33,7 +33,7 @@ to a shared latent space. The projection layers are randomly initialized so the
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downstream task. This model can be used to align the vision-text embeddings using CLIP like contrastive image-text
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training and then can be used for zero-shot vision tasks such image-classification or retrieval.
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In [LiT: Zero-Shot Transfer with Locked-image Text Tuning](https://arxiv.org/abs/2111.07991) it is shown how
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In [LiT: Zero-Shot Transfer with Locked-image Text Tuning](https://huggingface.co/papers/2111.07991) it is shown how
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leveraging pre-trained (locked/frozen) image and text model for contrastive learning yields significant improvement on
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new zero-shot vision tasks such as image classification or retrieval.
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