Instructions to use AIPeanutman/OpenSubject with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AIPeanutman/OpenSubject with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AIPeanutman/OpenSubject", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Commit History
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Add pipeline tag, library name, paper, and code links
Verified signatureThis PR enhances the model card by: - Adding `pipeline_tag: image-to-image` to improve discoverability for relevant tasks on the Hub. - Specifying `library_name: diffusers` due to evidence of compatibility (`_diffusers_version` in `config.json`), which will enable an automated usage snippet. - Including a direct link to the paper: [OpenSubject: Leveraging Video-Derived Identity and Diversity Priors for Subject-driven Image Generation and Manipulation](https://huggingface.co/papers/2512.08294). - Adding an explicit link to the GitHub repository for the code: [https://github.com/LAW1223/OpenSubject](https://github.com/LAW1223/OpenSubject). These changes improve the model's documentation and user experience on the Hugging Face Hub.9cd1bb0
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Update README.md
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Upload folder using huggingface_hub
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