let's deploy to huggingface spaces

app.py

@@ -0,0 +1,18 @@
+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('export.pkl')
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred, idx, probs = learn.predict(img)
+    return{labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Breed Classifier"
+description = "A animal/pet Breed Classifier"
+examples = ['cat.jpg.webp']
+interpretation = 'default'
+enable_queue = True
+
+gr.Interface(fn = predict, inputs = gr.Image(), outputs = gr.Label(num_top_classes = 3), title = title, description = description , examples = examples).launch(share=True)

export.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f262feb5ed7f76660ee523d5632b4112997242ddc56ae252793532a6d2d7333d
+size 103057580

requirements.txt

@@ -0,0 +1,2 @@
+fastai
+scikit-image