| --- |
| title: Probing-Vis-Literacy-of-VLMs |
| emoji: 🐨 |
| colorFrom: pink |
| colorTo: yellow |
| sdk: gradio |
| sdk_version: 5.20.0 |
| app_file: app.py |
| pinned: false |
| license: mit |
| --- |
| |
| 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 |
| ``` |
|
|
