Create app.py

app.py

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+import gradio as gr
+from huggingface_hub import hf_hub_download
+from fastai.learner import load_learner
+import os
+
+TOKEN = os.environ["token"]
+REPO_ID = "42digital/deepfashion_classification_vit-large-patch14-clip-336"
+FILENAME = "model.pkl"
+
+learner = load_learner(
+    hf_hub_download(repo_id=REPO_ID, filename=FILENAME, token=TOKEN)
+)
+
+def predict(img):
+    _, _, probs = learner.predict(img)
+    probs = [float(p) for p in probs.detach()]
+    preds = {k: v for k, v in zip(learner.dls.vocab, probs)}
+    return preds
+
+gr.Interface(fn=predict, 
+             inputs=gr.Image(type="numpy"),
+             outputs=gr.Label(num_top_classes=4),
+             examples=[]).launch()