let's deploy to huggingface spaces

export.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0382190a4647381f027bc601c2379c9a1b0616fccb26934cfede376329b2985d
+size 103946124

gradio_nsfw_classfier.py

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+#!/usr/bin/env python
+# coding: utf-8
+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('export.pkl')
+labels = learn.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+title = "NSFW image classifier"
+description = "A nsfw image classifier trained on the nsfw_data_scraper dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+interpretation='default'
+enable_queue=True
+
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512,512)),outputs=gr.outputs.Label(num_top_classes=5),title=title,description=description,interpretation=interpretation,enable_queue=enable_queue).launch(share=True)
+
+

requirments.txt

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+fastai
+scikit-image