44 lines
1.6 KiB
Docker
44 lines
1.6 KiB
Docker
# ROCm-enabled PyTorch base image from AMD
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# Pick a tag that matches your installed ROCm driver best; this one is a good default.
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FROM rocm/pytorch:rocm7.1.1_ubuntu22.04_py3.10_pytorch_release_2.9.1
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# OCI metadata for discoverability
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LABEL org.opencontainers.image.source="https://github.com/zuzupebbles/unsloth-rocm"
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LABEL org.opencontainers.image.url="https://hub.docker.com/r/zuzupebbles/unsloth-rocm"
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LABEL org.opencontainers.image.title="Unsloth ROCm image"
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LABEL org.opencontainers.image.description="Unsloth + ROCm PyTorch for AMD GPUs (e.g. 7900 XTX)"
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LABEL org.opencontainers.image.licenses="Apache-2.0"
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# Basic utilities
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RUN apt-get update && \
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DEBIAN_FRONTEND=noninteractive apt-get install -y \
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git wget curl vim nano && \
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rm -rf /var/lib/apt/lists/*
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# Upgrade pip and install Unsloth (AMD is supported via regular pip install)
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# Unsloth itself is Apache-2.0 licensed.
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RUN pip install --upgrade pip && \
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pip install --no-cache-dir unsloth
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# Optional: tools you’ll almost certainly want when experimenting
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RUN pip install --no-cache-dir \
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"transformers>=4.45.0" \
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datasets \
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accelerate \
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peft \
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safetensors \
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bitsandbytes || true
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# ^ bitsandbytes may be CUDA-only; failing here is fine, Unsloth on ROCm does not strictly need it.
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# Create a non-root user that matches your host UID/GID at runtime (set via docker-compose)
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ARG USERNAME=unsloth
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ARG UID=1000
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ARG GID=1000
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RUN groupadd -g ${GID} ${USERNAME} && \
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useradd -m -u ${UID} -g ${GID} -s /bin/bash ${USERNAME}
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USER ${USERNAME}
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WORKDIR /workspace
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# Keep the container alive by default; you’ll exec into it
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CMD ["bash"]
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