quote the skip step the install readme

mllam · Aug 20, 2024 · b96cfdc · b96cfdc
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commit b96cfdc
Showing 1 changed file with 4 additions and 2 deletions.
diff --git a/README.md b/README.md
@@ -77,14 +77,16 @@ setup](.github/workflows/) which you can use as a reference.
 ### Using `pdm`
 
 1. Clone this repository and navigate to the root directory.
-2. Install `pdm` if you don't have it installed on your system (either with `pip install pdm` or [following the install instructions](https://pdm-project.org/latest/#installation)). If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 5.
+2. Install `pdm` if you don't have it installed on your system (either with `pip install pdm` or [following the install instructions](https://pdm-project.org/latest/#installation)).
+> If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 5.
 3. Create a virtual environment for pdm to use with `pdm venv create --with-pip`.
 4. Install a specific version of `torch` with `pdm run python -m pip install torch --index-url https://download.pytorch.org/whl/cpu` for a CPU-only version or `pdm run python -m pip install torch --index-url https://download.pytorch.org/whl/cu111` for CUDA 11.1 support (you can find the correct URL for the variant you want on [PyTorch webpage](https://pytorch.org/get-started/locally/)).
 5. Install the dependencies with `pdm install` (by default this in include the). If you will be developing `neural-lam` we recommend to install the development dependencies with `pdm install --group dev`. By default `pdm` installs the `neural-lam` package in editable mode, so you can make changes to the code and see the effects immediately.
 
 ### Using `pip`
 
-1. Clone this repository and navigate to the root directory. If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 3.
+1. Clone this repository and navigate to the root directory.
+> If you are happy using the latest version of `torch` with GPU support (expecting the latest version of CUDA is installed on your system) you can skip to step 3.
 2. Install a specific version of `torch` with `python -m pip install torch --index-url https://download.pytorch.org/whl/cpu` for a CPU-only version or `python -m pip install torch --index-url https://download.pytorch.org/whl/cu111` for CUDA 11.1 support (you can find the correct URL for the variant you want on [PyTorch webpage](https://pytorch.org/get-started/locally/)).
 3. Install the dependencies with `python -m pip install .`. If you will be developing `neural-lam` we recommend to install in editable mode and install the development dependencies with `python -m pip install -e ".[dev]"` so you can make changes to the code and see the effects immediately.