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chris 2024-09-21 11:14:51 +02:00
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@ -16,8 +16,9 @@ docker build -t cuda-unsloth-jupyter .
And mount your directory to the ```/app``` path when starting.
Setting default password to: `123`
```shell
docker run --rm --gpus=all -v path_to_files:/app -d cuda-unsloth-jupyter
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.
@ -28,3 +29,7 @@ Currently tested with:
| GPU Model | Memory (GB) |
|-------------|-------------|
| RTX 3090 Ti | 24 |
Please note:<br>
If you are using a different graphics card or a different Pytorch version, then you must adapt the Dockerfile accordingly. See:
[docs.unsloth.ai](https://docs.unsloth.ai/get-started/installation/pip-install)