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https://github.com/hiyouga/LLaMA-Factory.git
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Intel docker file (#10753)
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48
docker/docker-xpu/docker-compose.yml
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48
docker/docker-xpu/docker-compose.yml
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services:
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llamafactory:
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build:
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dockerfile: ./docker/docker-xpu/Dockerfile
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context: ../..
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args:
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PIP_INDEX: https://pypi.org/simple
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# The DLE base image determines which Intel GPU runtime (libze-intel-gpu)
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# is shipped. The runtime version must be >= the host driver version,
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# otherwise torch.xpu.device_count() returns 0:
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# DLE 2025.3 → libze-intel-gpu 25.18.x (works on driver ≤26.09)
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# DLE 2026.1 → libze-intel-gpu 26.18.x+ (works on driver 26.18/26.22)
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# Verify host driver: dpkg -l libze-intel-gpu1 | grep -oP '\d+\.\d+\.\d+'
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BASE_IMAGE: intel/deep-learning-essentials:2026.1.0-devel-ubuntu24.04
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container_name: llamafactory
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image: llamafactory:xpu
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ports:
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- "7860:7860"
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- "8000:8000"
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ipc: host
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tty: true
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# shm_size: "16gb" # ipc: host is set
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stdin_open: true
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command: bash
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devices:
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# Intel GPU character devices (renderD* and card* under /dev/dri).
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# renderD* nodes are owned by group `render`; card* by group `video`.
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- /dev/dri:/dev/dri
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volumes:
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# by-path symlinks are required for oneCCL's ze_fd_manager (2-GPU IPC).
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# `devices:` alone does not carry sub-directories — this volume does.
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- /dev/dri/by-path:/dev/dri/by-path
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- ~/.cache/huggingface:/root/.cache/huggingface
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group_add:
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# Grant access to the Intel GPU device nodes.
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# renderD* nodes are owned by group `render`; card* nodes by `video`.
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# Use numeric GIDs here — Docker compose resolves group names against
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# the CONTAINER's /etc/group (not the host), and the DLE base image
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# does not carry a `render` group entry. Standard Linux GIDs:
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# If your host uses different GIDs, run `getent group render video` and
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# update these values accordingly.
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# example output.
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# getent group render video
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# render:x:992:root
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# video:x:44:support
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- "992" # render — owns /dev/dri/renderD* nodes
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- "44" # video — owns /dev/dri/card* nodes
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restart: unless-stopped
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