deploy to huggingface spaces

app.py

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+__all__ = ['is_cat', 'learn', 'classify_image', 'categories', 'image', 'labels', 'examples', 'intf']
+
+from fastai.vision.all import *
+import gradio as gr
+
+# labelling function
+def is_cat(x): return x[0].isupper()
+
+learn = load_learner('model.pkl')
+
+# create categories and classifying function for HuggingFace Space
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    # gradio wants a dictionary
+    return dict(zip(categories, map(float, probs)))
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg', 'hybrid.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs = image, outputs = label, examples = examples)
+intf.launch(inline = False)

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:9a0b8910baa00a4b0d577c478292cf815877403fd8d7572e37ae55c138815911
+size 47065323

requirements.txt

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+fastai