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Merge pull request #160 from d-kleine/main

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small changes Docker / OpenAI
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Sebastian Raschka 2024-05-17 07:51:26 -04:00 committed by GitHub
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2
ch05/02_alternative_weight_loading/README.md
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@ -1,5 +1,5 @@
# Alternative Weight Loading
This folder contains alternative weight loading strategies in case the weights become unavailable from Open AI.
This folder contains alternative weight loading strategies in case the weights become unavailable from OpenAI.
- [weight-loading-hf-transformers.ipynb](weight-loading-hf-transformers.ipynb): contains code to load the weights from the Hugging Face Model Hub via the `transformers` library

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setup/03_optional-docker-environment/README.md
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@ -27,17 +27,20 @@ git clone https://github.com/rasbt/LLMs-from-scratch.git
cd LLMs-from-scratch
```
2. Move the `.devcontainer` folder from `setup/03_optional-docker-environment/` to the current directory (project root).
```bash
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:
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": {
@ -46,6 +49,7 @@ mv setup/03_optional-docker-environment/.devcontainer ./
```
For example, the full Docker Engine daemon config json code should look like that:
```json
{
"builder": {
@ -63,11 +67,12 @@ mv setup/03_optional-docker-environment/.devcontainer ./
}
}
```
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.
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.