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added missing step 2 and prettyfied readme

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Daniel Kleine 2024-05-17 10:43:35 +02:00
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setup/03_optional-docker-environment/README.md
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@ -27,47 +27,52 @@ git clone https://github.com/rasbt/LLMs-from-scratch.git
cd LLMs-from-scratch cd LLMs-from-scratch
``` ```
2. Move the `.devcontainer` folder from `setup/03_optional-docker-environment/` to the current directory (project root).
```bash ```bash
mv setup/03_optional-docker-environment/.devcontainer ./ mv setup/03_optional-docker-environment/.devcontainer ./
``` ```
3. In Docker Desktop, make sure that ***desktop-linux* builder** is running and will be used to build the Docker container (see *Docker Desktop* -> *Change settings* -> *Builders* -> *desktop-linux* -> *...* -> *Use*) 3. In Docker Desktop, make sure that **_desktop-linux_ builder** is running and will be used to build the Docker container (see _Docker Desktop_ -> _Change settings_ -> _Builders_ -> _desktop-linux_ -> _..._ -> _Use_)
4. If you have a [CUDA-supported GPU](https://developer.nvidia.com/cuda-gpus), you can speed up the training and inference: 4. If you have a [CUDA-supported GPU](https://developer.nvidia.com/cuda-gpus), you can speed up the training and inference:
3.1 Install **NVIDIA Container Toolkit** as described [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-apt). NVIDIA Container Toolkit is supported as written [here](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#nvidia-compute-software-support-on-wsl-2). 3.1 Install **NVIDIA Container Toolkit** as described [here](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-apt). NVIDIA Container Toolkit is supported as written [here](https://docs.nvidia.com/cuda/wsl-user-guide/index.html#nvidia-compute-software-support-on-wsl-2).
3.2 Add *nvidia* as runtime in Docker Engine daemon config (see *Docker Desktop* -> *Change settings* -> *Docker Engine*). Add these lines to your config: 3.2 Add _nvidia_ as runtime in Docker Engine daemon config (see _Docker Desktop_ -> _Change settings_ -> _Docker Engine_). Add these lines to your config:
```json
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
```
For example, the full Docker Engine daemon config json code should look like that: ```json
```json "runtimes": {
{ "nvidia": {
"builder": { "path": "nvidia-container-runtime",
"gc": { "runtimeArgs": []
"defaultKeepStorage": "20GB", ```
"enabled": true
} For example, the full Docker Engine daemon config json code should look like that:
},
"experimental": false, ```json
"runtimes": { {
"nvidia": { "builder": {
"path": "nvidia-container-runtime", "gc": {
"runtimeArgs": [] "defaultKeepStorage": "20GB",
} "enabled": true
} }
} },
``` "experimental": false,
and restart Docker Desktop. "runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
}
}
```
and restart Docker Desktop.
5. Type `code .` in the terminal to open the project in VS Code. Alternatively, you can launch VS Code and select the project to open from the UI. 5. Type `code .` in the terminal to open the project in VS Code. Alternatively, you can launch VS Code and select the project to open from the UI.
6. Install the **Remote Development** extension from the VS Code *Extensions* menu on the left-hand side. 6. Install the **Remote Development** extension from the VS Code _Extensions_ menu on the left-hand side.
7. Open the DevContainer. 7. Open the DevContainer.