Instructions to use ByteDance/ID-Patch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/ID-Patch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/ID-Patch", 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
metadata
license: openrail++
Model Card for ID-Patch
ID-Patch is a diffusion model capable of generating ID-preserving group photos
Model Details
Please refer our github repository for more details and how to use this model.
- Repository: https://github.com/bytedance/ID-Patch
- Paper: https://arxiv.org/abs/2411.13632
License
The model is released under CreativeML Open RAIL++-M License