Python environment not easy to set up with requirements for Llama examples

Hello,

First: thanks for creating this repo and initiative to show concrete examples of MLX at work!

Running the Llama examples, and following the doc to install Python packages, I ran into issues of missing packages (especially if using HuggingFace and skipping the step of model weight conversions).

Would you be interested if I shared a Poetry Python env that I created?

Pros:

• have a Python virtual env setup in a one-liner with poetry install
• accessible to everyone, without the cost of having to install and fix Python environment issues -> it can help democratize MLX by lower the installation cost
• setting up Python env with Pyenv, or Poetry, is now considered a better practice than pip + requirements.txt

Cons

• poetry would be an added dependency to the project, but it can be as simple as brew install poetry

I'd be happy to collaborate by starting with a dedicated env for the Llama example if you believe it's a good idea.

Thank you!

Start with the documentation for running the Llama examples and the requirements used by those examples, especially the HuggingFace and model-conversion paths. Evaluate the proposed Poetry environment and its added dependency; done means the documented setup installs the packages needed for the Llama examples in one command.