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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          |