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
Add pipeline tag, library name, paper, and code links
#1
by nielsr HF Staff - opened
This PR enhances the model card by:
- Adding
pipeline_tag: image-to-imageto improve discoverability for relevant tasks on the Hub. - Specifying
library_name: diffusersdue to evidence of compatibility (_diffusers_versioninconfig.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.
- Adding an explicit link to the GitHub repository for the code: https://github.com/LAW1223/OpenSubject.
These changes improve the model's documentation and user experience on the Hugging Face Hub.