working version

.mambarc

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+channels:
+  - conda-forge
+always_yes: false

README.md

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 ---
 license: apache-2.0
-pipeline_tag: image-classification
----
+---

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import logging
+
+
+def is_cat(x): return x[0].isupper()
+
+learn = load_learner('model.pkl')
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    logging.info(pred, probs)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+demo = gr.Interface(
+  fn=predict,
+  inputs=gr.Image(),
+  outputs=gr.Label(num_top_classes=3)
+)
+
+demo.launch()