Add Pruna AI library snippets (no formatting changes)

[davidberenstein1957]

This update enhances support for Pruna AI, providing users with tailored code snippets for model integrations with Transformers and Diffusers.

• Introduced a new library entry for Pruna AI in model-libraries.
• Added main entry point and specific snippet generation functions for diffusers and transformers models.
• Cleaned up whitespace inconsistencies in existing snippets.

TLDR: Pruna API normally mimics the Transformers and Diffusers API, so we can use PrunaModel.from_pretrained on top of pipelines or specific models. We re-use the underlying snippets for both the library and do some greedy replacements of certain part of the code snippets.

example

import torch
from diffusers import FluxFillPipeline
from diffusers.utils import load_image

image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")

pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("cuda")
image = pipe(
    prompt="a white paper cup",
    image=image,
    mask_image=mask,
    height=1632,
    width=1232,
    guidance_scale=30,
    num_inference_steps=50,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save(f"flux-fill-dev.png")

becomes

import torch
from pruna import PrunaModel
from diffusers.utils import load_image

image = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup.png")
mask = load_image("https://huggingface.co/datasets/diffusers/diffusers-images-docs/resolve/main/cup_mask.png")

pipe = PrunaModel.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16).to("cuda")
image = pipe(
    prompt="a white paper cup",
    image=image,
    mask_image=mask,
    height=1632,
    width=1232,
    guidance_scale=30,
    num_inference_steps=50,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save(f"flux-fill-dev.png")

[Wauplin]

I did not check the diffusers/transformers snippets themselves but the PR looks good. I left a few comments to address but that's all :)

And thanks for opening a separate PR without reformatting!

[Wauplin]

Looks good! I'll merge once lint CI is green :)

[Wauplin]

(expect 2-3 days before getting it live on the Hub)