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vit-finetuned-space
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import gradio as gr

examples = ["https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/oGDkcC_A2EippXY1qGzvz.png",
           "https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/Q7KrLHxyOGGMYe9Il-AGr.png",
           "https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/eeBiP6moG6h-f2JMcWFVq.png",
           "https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/Kh3W61A0j8mjtkmeaclnP.png",
           "https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/8WTccefRQ1AJVXh1tv9Tt.png",
           "https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/wXoSxoNaOZwUpvoCFosEm.png",
           "https://cdn-uploads.huggingface.co/production/uploads/63de2ecce742e86dc9196cb0/ya4D9ZiChtk2EHdxY8Eki.png"]

description = "This demo uses a Vision Transformer model specially trained for breast cancer detection. You can see the model's predictions by uploading an X-ray image below."

gr.load("models/emre570/google-vit-large-finetuned", 
        title="Fine Tuned Breast Cancer ViT Demo",
        description = description,
        examples = examples).launch()