I made a pipeline that lets you use any number of models at once

### Model/Pipeline/Scheduler description

Here's how to do it:
from rubberDiffusers import StableDiffusionRubberPipeline
pipe=StableDiffusionRubberPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32,local_files_only=True,safety_checker=None, requires_safety_checker=False,
)

pipe2=StableDiffusionRubberPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32,local_files_only=True,safety_checker=None, requires_safety_checker=False,
)

apply_multiModel(pipe)
pipe.added_model=[pipe2]
image=pipe("your prompt",width=512,height=512,pos=["0:0-512:512"],mask_strengths=[.5],model_kwargs=[{prompt="your prompt for the first loaded model"}]).images[0]

### Open source status

- [ ] The model implementation is available.
- [ ] The model weights are available (Only relevant if addition is not a scheduler).

### Provide useful links for the implementation

https://github.com/alexblattner/RubberDiffusers

The issue points to the external RubberDiffusers implementation rather than naming a diffusers file, test, or entry point. Start by reviewing that linked implementation and comparing it with the repository's pipeline architecture. A scoped integration target and acceptance criteria are needed before completion can be defined.

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