Update README.md

README.md

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 # BiomedCLIP-PubMedBERT_256-vit_base_patch16_224
 
-[BiomedCLIP](https://aka.ms/biomedclip-paper) is a biomedical vision-language foundation model that is pretrained on [PMC-15M](https://aka.ms/biomedclip-paper) dataset using contrastive learning. It uses PubMedBERT as the text encoder and Vision Transformer as the image encoder, with domain-specific adaptations. It can perform various biomedical tasks such as cross-modal retrieval, image classification, and visual question answering. It achieves state-of-the-art results on several biomedical benchmarks, outperforming general-domain models and radiology-specific models.
+[BiomedCLIP](https://aka.ms/biomedclip-paper) is a biomedical vision-language foundation model that is pretrained on [PMC-15M](https://aka.ms/biomedclip-paper) dataset using contrastive learning.
+It uses PubMedBERT as the text encoder and Vision Transformer as the image encoder, with domain-specific adaptations.
+It can perform various vision-language processing (VLP) tasks such as cross-modal retrieval, image classification, and visual question answering. 
+BiomedCLIP establishes new state of the art in a wide range of standard datasets, and substantially outperforms prior VLP approaches.
 
 ## Citation