Added the model, examples, and requirements

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('model_v4_98_percent_final.pkl')
+
+categories = ('lotad', 'quagsire', 'slowpoke', 'snorlax')
+
+def classify_image(img):
+  pred, idx, probs = learn.predict(img)
+  return dict(zip(categories, map(float, probs)))
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['lotad.jpg', 'quagsire.jpg', 'slowpoke.jpg', 'snorlax.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()

model_v4_98_percent_final.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ae3dd67364a7a22cd182b3ca021e5c10eb82bdc5d2943b0c88c0986aa4799852
+size 87484773

requirements.txt

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+fastai
+gradio