Instructions to use LongfeiHuang/SDMatte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LongfeiHuang/SDMatte 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("LongfeiHuang/SDMatte", 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
Commit History
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Add comprehensive model card for SDMatte
Verified signatureThis PR adds a comprehensive model card for the SDMatte model, significantly improving its documentation and discoverability on the Hugging Face Hub. It includes the following key updates: - **Relevant Metadata**: Adds `pipeline_tag: image-to-image` and `library_name: diffusers` to the YAML metadata. This allows the model to be easily found by users filtering by pipeline type and indicates its compatibility with the popular 🤗 Diffusers library. - **Paper Details**: Integrates the paper title, a link to the Hugging Face paper page ([SDMatte: Grafting Diffusion Models for Interactive Matting](https://huggingface.co/papers/2508.00443)), and the full abstract, providing essential context about the model. - **Code Link**: Adds a direct link to the official GitHub repository for SDMatte (`https://github.com/chen-sd/SDMatte`), as mentioned in the paper's abstract. - **Basic Usage Example**: Provides a conceptual Python usage example with the `diffusers` library to guide users on how to load…1a86f20
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upload configs
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initial commit
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