import torch
from huggingface_hub import hf_hub_download

# Download and load
model_path = hf_hub_download("Khauneesh/tiny-cnn-torchscript", "model.pt")
model = torch.jit.load(model_path, map_location="cpu")
model.eval()

# Inference
x = torch.randn(1, 3, 224, 224)
with torch.no_grad():
    logits = model(x)

Testing

Architecture: Simple 3-layer CNN (TinyCNN)
Input: [1, 3, 224, 224] float32 tensor (RGB image)
Output: [1, 10] logits (10 classes)
Format: TorchScript (traced)

This model is designed for smoke testing TorchScript deployment pipelines.