Instructions to use wangfuyun/Diffusion-NPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wangfuyun/Diffusion-NPO with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wangfuyun/Diffusion-NPO", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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Add model card for Self-NPO (Diffusion-NPO)
Verified signatureThis PR adds a comprehensive model card for **Self-NPO**, a data-free negative preference optimization approach, which is part of the broader **Diffusion-NPO** framework. The update includes: - A link to the paper: [Self-NPO: Data-Free Diffusion Model Enhancement via Truncated Diffusion Fine-Tuning](https://huggingface.co/papers/2505.11777). - Relevant metadata: `license` (Apache 2.0), `pipeline_tag` (text-to-image), and `library_name` (diffusers). - The full abstract of the paper. - An overview and key features of the model, extracted from the GitHub README. - A detailed sample usage section for inference, with code snippets directly from the GitHub repository. - Example outputs, Model Zoo, Citation, and License information from the GitHub README. This model card significantly improves the discoverability and usability of the model on the Hugging Face Hub.651e5ff
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