File	Format	Use
`best.pth`	PyTorch state dict	training / fine-tuning
`model.torchscript.pt`	TorchScript	server / LibTorch
`model_mobile.ptl`	TorchScript Lite	iOS / Android (PyTorch Mobile)
`model.onnx`	ONNX	Core ML, TFLite (via onnx2tf), ONNX Runtime Mobile

Inference (Python)

python

import torch, torchvision.transforms as T
from PIL import Image
m = torch.jit.load("model.torchscript.pt").eval()
tf = T.Compose([T.Resize((224,224)), T.ToTensor(),
                T.Normalize([0.485,0.456,0.406],[0.229,0.224,0.225])])
img = tf(Image.open("food.jpg").convert("RGB")).unsqueeze(0)
probs = torch.softmax(m(img), dim=-1)[0]
print({"healthy": probs[0].item(), "unhealthy": probs[1].item()})

maia2000/food-classifier-binary-vit

Binary Healthy/Unhealthy Food Classifier — ViT-B/16

Test metrics

Files

Inference (Python)

maia2000/
food-classifier-binary-vit