It feels like forever since I was last looking into the fast.ai library. So, I’m resorting to start over my understanding from scratch, building a multi class classification model.
I also saw some Huggingface spaces demos a while ago, and thought that was pretty neat. Earlier this week when looking into it, I found out that it was definitely possible to use fast.ai models on huggingface spaces via gradio, so I figured why not try that.
So, what I’ve done is built a Food image classifier (Food-101 dataset) and hosted it as a live interactive demo on HF spaces. I find it more fun to be able to play around with the model with real images.
Live demo at : Food Image Classifier (Food-101|ResNet50|fast.ai) - a Hugging Face Space by suvash
Let me know what you think. If there’s enough interest, I can share the notebook as well. It’s very similar to the classifying breeds tutorial on fastai docs.
Overall, this was fun to build. 
EDIT : I’ve now also added the notebooks used for training (and testing out gradio inference) in the same HF repo (notebooks folder) if anybody wants to take a look at it.