diff --git a/setup/01_optional-python-setup-preferences/README.md b/setup/01_optional-python-setup-preferences/README.md index a7a08fe..211cf2a 100644 --- a/setup/01_optional-python-setup-preferences/README.md +++ b/setup/01_optional-python-setup-preferences/README.md @@ -4,6 +4,13 @@ There are several ways to install Python and set up your computing environment. Here, I share my personal preferences. +
+ +> [!NOTE] If you are running any of the notebooks on Google Colab and want to install the dependencies, simply run the following code in a new cell at the top of the notebook and skip the rest of this tutorial: +> `pip install uv && uv pip install --system -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/refs/heads/main/requirements.txt` + +The remaining sections below describe how you can manage your Python environment and packages on your local machine. + I have been a long-time user of [Conda](https://anaconda.org/anaconda/conda) and [pip](https://pypi.org/project/pip/), but recently, the [uv](https://github.com/astral-sh/uv) package has gained significant traction as it provides a faster and more efficient way to install packages and resolve dependencies. I recommend starting with *Option 1: Using uv* as it is the more modern approach in 2025. If you encounter problems with *Option 1*, consider *Option 2: Using Conda*. diff --git a/setup/README.md b/setup/README.md index 2514750..3dbda07 100644 --- a/setup/README.md +++ b/setup/README.md @@ -13,6 +13,12 @@ If you already have a Python installation on your machine, the quickest way to g pip install -r requirements.txt ``` +
+ +> [!NOTE] If you are running any of the notebooks on Google Colab and want to install the dependencies, simply run the following code in a new cell at the top of the notebook: +> `pip install uv && uv pip install --system -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/refs/heads/main/requirements.txt` + +   # Local Setup