unsloth-rocm 🦥🔥

Unsloth + PyTorch-on-ROCm in a ready-to-use Docker image for AMD GPUs
(Navi / RDNA2 / RDNA3 – e.g. 7900 XTX).

• Base image: rocm/pytorch (PyTorch with ROCm backend)
• Fine-tuning framework: Unsloth (Apache-2.0).

This repo contains:

• Dockerfile – how the image is built
• docker-compose.build.yml – a sample compose file for local build + dev use

The idea is to give ROCm users a “batteries-included” Unsloth container and a clean example of how to wire up devices / groups / HF cache.

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Requirements

On the host (e.g. Arch, Ubuntu, etc.):

• AMD GPU supported by ROCm / rocm/pytorch (MI* or newer Navi, see AMD’s support matrix)
• ROCm stack installed and working (rocminfo sees your GPU)
• Docker or compatible container runtime
• User is in the appropriate groups, e.g.:

  sudo usermod -aG video,docker $USER
  # log out & back in afterwards

You should also see /dev/kfd and /dev/dri on the host:

ls /dev/kfd
ls /dev/dri

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Build locally

Clone the repo (whichever remote you like – GitHub or your local Forgejo):

git clone https://github.com/zuzupebbles/unsloth-rocm.git
cd unsloth-rocm

Build the image:

# ensure UID/GID match your host user (especially on Arch)
export UID
export GID

docker compose -f docker-compose.build.yml build

This will produce a local image named:

zuzupebbles/unsloth-rocm:local

You can confirm with:

docker images | grep unsloth-rocm

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Run for local dev

Bring up a dev container:

docker compose -f docker-compose.build.yml up -d
docker compose -f docker-compose.build.yml exec unsloth-rocm bash

Inside the container you’ll have:

• user: unsloth

• working dir: /workspace

• volumes mounted:

  • ./workspace → /workspace
  • ~/.cache/huggingface → /data/hf-cache
  • ./repos-clone → /repos-clone

Quick sanity check in the container:

python -c "import torch; print(torch.cuda.is_available(), torch.version.cuda, torch.version.hip, torch.version.git_version)"
python -c "import unsloth; print(unsloth.__version__)"

(ROCm builds often report HIP instead of CUDA, that’s expected.)