Fix: Align model and input data types to float16 for inference

#9

Description

This PR fixes a runtime error in the example code caused by a mismatch between the input tensor type and the model weights during inference.

Changes

  • Converted the model to float16:
    model = model.to("cuda").half()

  • Converted float32 input tensors from the processor to float16:
    inputs = {k: v.half() if isinstance(v, torch.Tensor) and v.dtype == torch.float32 else v for k, v in inputs.items()}

Testing

The code has been successfully tested and runs without error.

Note

This contribution is part of an ongoing research initiative to systematically identify and correct faulty example code in Hugging Face Model Cards.
We would appreciate a timely review and integration of this patch to support code reliability and enhance reproducibility for downstream users.

Ready to merge
This branch is ready to get merged automatically.

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