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uw-insight-lab/Probing-Vis-Literacy-of-VLMs

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App README

Check out the configuration reference at <https://huggingface.co/docs/hub/spaces-config-reference>

Docker GPU runtime

The container is pinned to PyTorch 2.9.1 with CUDA 13.0 for NVIDIA Blackwell/RTX 50-series compatibility.

Requirements:

  • —NVIDIA driver compatible with CUDA 13.0
  • —Docker Desktop with the WSL2 backend on Windows
  • —NVIDIA GPU access enabled in Docker

Build and run:

shell
docker compose build
docker compose up

Open <http://localhost:7860>. The entry point executes a CUDA kernel before starting Gradio and exits with an actionable error if the GPU is unavailable.

To validate Docker GPU passthrough independently:

shell
docker run --rm --gpus all nvidia/cuda:13.0.0-base-ubuntu22.04 nvidia-smi