Safetensors
clip
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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
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  ---
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- Initialized with RCLIP/OpenCLIP-ViT-g-rho50-k1 and trained with FARE2 for 0.5 epoch on ImageNet, bs 64
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ license: mit
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+ datasets:
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+ - ILSVRC/imagenet-1k
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+ - mlfoundations/datacomp_small
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+ base_model:
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+ - laion/CLIP-ViT-g-14-laion2B-s34B-b88K
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  ---
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+ Model Initialized from `laion/CLIP-ViT-g-14-laion2B-s34B-b88K`. The image encoder is finetuned with FARE at $\epsilon=2/255$. The text encoder is finetuned with LEAF at $k=1$ with $\rho=50$.
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+ To load this model use:
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+
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+ ```python
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+ from transformers import CLIPProcessor, CLIPModel
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+
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+ model_name = "LEAF-CLIP/OpenCLIP-ViT-g-rho50-k1-FARE2"
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+ processor_name = "laion/CLIP-ViT-g-14-laion2B-s34B-b88K"
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+
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+ model = CLIPModel.from_pretrained(model_name)
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+ processor = CLIPProcessor.from_pretrained(processor_name)
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+ ```