update

app.py

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+import gradio as gr
+from fastai.vision.all import load_learner, PILImage
+
+# Load the pre-trained FastAI model
+model_path = "path_to_your_fastai_model.pkl"
+learn = load_learner(model_path)
+
+# Define the prediction function
+def predict(image):
+    img = PILImage.create(image)
+    pred_class, pred_idx, probs = learn.predict(img)
+    return f"Prediction: {pred_class}, Probability: {probs[pred_idx]:.4f}"
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="file"),
+    outputs="text",
+    title="Image validation",
+    description="Upload an image and get the model's text prediction."
+)
+
+demo.launch()