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app.py

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+import gradio as gr
+from fastai.vision.all import *
+from huggingface_hub import from_pretrained_fastai
+
+
+learn = from_pretrained_fastai("Pablogps/castle-classifier-24")
+labels = learn.dls.vocab
+
+
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+title = "Bad castle predictor"
+description = "A bad model that tries to identify the type of castle."
+examples = ['spanish', 'french', 'japanese']
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.Image(),
+    outputs=gr.Label(num_top_classes=3),
+    title=title,
+    description=description,
+    examples=examples,
+).launch()

requirements.txt

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+timm
+fastai
+toml