unsloth-rocm/Dockerfile

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