Fastai is essentially a wrapper around PyTorch, so there’s no fastai + PyTorch, only PyTorch. As far as I’m aware, Coral TPUs are only compatible with TensorFlow, but you could write/train the bulk of your model in PyTorch, convert it to TensorFlow with ONNX, and do the rest in TensorFlow. Alas, ONNX may prove to be quite tricky, and you’d still have to work with TensorFlow at some point, so you could argue this is the worst of both worlds.
If you don’t want to go near TensorFlow (completely understandable), I think the Jetson Nano is your best bet since it supports PyTorch and has an active community. Beware though, I’ve been dabbling with TinyML & microcontrollers for a while, and TensorFlow (TensorFlow Lite and TensorFlow Lite for Microcontrollers specifically) is much more mature for deployment on Edge devices, pruning, quantization, etc. For the time being at least, it wouldn’t hurt to learn TF and give it a shot.
Hopefully this helps!