Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the breast cancer image classification model
+model = pipeline("image-classification", model="OverDriveLee/Breast_Cancer")
+
+# Define the prediction function
+def classify_image(image):
+    results = model(image)
+    return {"prediction": results[0]["label"], "confidence": results[0]["score"]}
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=classify_image,
+    inputs=gr.inputs.Image(),
+    outputs="json",
+    title="Breast Cancer Image Classification",
+    description="This application classifies breast cancer images into different classes."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    iface.launch()