HelperSheets/docker/unsloth
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Unsloth in a docker container

Very important

The complete docker image is designed for CUDA 12.1! There must be a compatible version on the host such as CUDA 12.2 and docker has to be installed.

Run nvidia-smi on the Host to see if you are using the right Conda version.

nvidia-smi

Build the container with:

docker build -t cuda-unsloth-jupyter .

And mount your directory to the /app path when starting.

Setting default password to: 123

docker run --rm  --gpus=all -v path_to_files:/app -e JUPYTER_TOKEN='123' -p 8088:8088 -d cuda-unsloth-jupyter

--rm: This flag automatically deletes the container after it exits, freeing up disk space and keeping the environment clean. Add the -it flag to run the container in interactive mode, giving you direct access to its shell. Use -d to detach the container and run it in the background. Combining -itd allows you to interact with the container initially, then detach, leaving it running in the background.

Currently tested with:

GPU Model Memory (GB)
RTX 3090 Ti 24

Please note:
If you are using a different graphics card or a different Pytorch version, then you must adapt the Dockerfile accordingly. See: docs.unsloth.ai