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# Unsloth in a docker container
❗ Very important ❗
The complete docker image is designed for CUDA 12.1!
On the Host there has to be <span style="color: red;">CUDA 12.1</span> and <span style="color: skyblue;">docker</span> installed.
Run `nvidia-smi` on the Host to see if you are using the right Conda version.
![nvidia-smi](./assets/nvidiasmi.png)
Build the container with:
```shell
docker build -t cuda-unsloth-jupyter .
```
And mount your directory to the ```/app``` path when starting.
```shell
docker run --rm --gpus=all -v path_to_files:/app -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 |