🧑‍🍳 New Cookbook Recipe: Add a recipe showcasing the usage of Pruna with Diffusers

[pruna](https://github.com/PrunaAI/pruna) is a library which contains a comprehensive suite of compression algorithms including [caching](https://docs.pruna.ai/en/stable/compression.html#cachers), [quantization](https://docs.pruna.ai/en/stable/compression.html#quantizers), [pruning](https://docs.pruna.ai/en/stable/compression.html#pruners), [distillation](https://docs.pruna.ai/en/stable/compression.html#distillers) and [compilation](https://docs.pruna.ai/en/stable/compression.html#compilers) techniques to make your models more efficient to use. I would be interested in contributing a recipe using pruna and the [diffusers](https://huggingface.co/docs/diffusers/index) library.

Based on a discussion with @davidberenstein1957, the recipe would feature a diffusers model quantized using the [smash](https://docs.pruna.ai/en/stable/docs_pruna/user_manual/configure.html) config, then the smashed model could be used for synthetic dataset creation, or we could evaluate the model against its unquantized version as well. Could you please let me know your thoughts and suggestions if the scope of the recipe is sufficient or any changes to make it more applied as well.

cc: @stevhliu

Review the linked Pruna compression and configuration documentation alongside the Diffusers documentation first, then clarify the recipe scope with maintainers. Done means a cookbook recipe demonstrates a Diffusers model quantized with the smash configuration and either uses it for synthetic dataset creation or evaluates it against the unquantized model.

Written by the indexing model from the issue text.