Instructions to use FireRedTeam/FireRed-Image-Edit-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FireRedTeam/FireRed-Image-Edit-1.0 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("FireRedTeam/FireRed-Image-Edit-1.0", 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name, and paper link to metadata
#3
by nielsr HF Staff - opened
This PR improves the model card by:
- Adding the
image-to-imagepipeline tag for better discoverability. - Adding
library_name: diffusersas the model structure is compatible with the library. - Adding the ArXiv ID to the metadata to link the model with its technical report.
- Updating the top navigation links to provide easy access to the official GitHub repository and the Hugging Face Papers page.