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@@ -11,6 +11,8 @@ Zero-shot ImageNet-1k top-1 accuracy: 34.642% (slightly better than the paper sc
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  - Paper: https://openreview.net/forum?id=ft1mr3WlGM
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  - GitHub: https://github.com/naver-ai/pcmepp
 
 
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  ```python
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  import requests
@@ -24,7 +26,10 @@ from hf_models import HfPCMEPPModel, tokenize
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  processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch16")
 
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  model = HfPCMEPPModel.from_pretrained("SanghyukChun/PCMEPP-ViT-B-16-CC3M-12M-RedCaps")
 
 
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  url = "http://images.cocodataset.org/val2017/000000039769.jpg"
 
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  - Paper: https://openreview.net/forum?id=ft1mr3WlGM
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  - GitHub: https://github.com/naver-ai/pcmepp
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+ - Check a better version with ImageNet-1k top-1 accuracy 41.812% (mean-only ZS classification) at [SanghyukChun/PCMEPP-ViT-B-16-CC3M-12M-RedCaps-256M](https://huggingface.co/SanghyukChun/PCMEPP-ViT-B-16-CC3M-12M-RedCaps-256M)
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  ```python
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  import requests
 
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  processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch16")
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+ # IN-top1: 34.64%
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  model = HfPCMEPPModel.from_pretrained("SanghyukChun/PCMEPP-ViT-B-16-CC3M-12M-RedCaps")
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+ # IN-top1: 41.81%
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+ # model = HfPCMEPPModel.from_pretrained("SanghyukChun/PCMEPP-ViT-B-16-CC3M-12M-RedCaps-256M")
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  url = "http://images.cocodataset.org/val2017/000000039769.jpg"