Instructions to use LiuZichen/MagicQuill-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LiuZichen/MagicQuill-models with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LiuZichen/MagicQuill-models", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, link to paper
Browse filesThis PR ensures the model can be found at https://huggingface.co/models?pipeline_tag=image-to-image&sort=trending and is linked to https://huggingface.co/papers/2411.09703.
README.md
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license: cc-by-nc-4.0
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Model Checkpoints for [project](https://github.com/magic-quill/MagicQuill).
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license: cc-by-nc-4.0
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pipeline_tag: image-to-image
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Model Checkpoints for [project](https://github.com/magic-quill/MagicQuill).
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The paper is [MagicQuill: An Intelligent Interactive Image Editing System](https://huggingface.co/papers/2411.09703).
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