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
有没有计划退出4steps 或者 8steps 的加速版本?
#10
by zhiyaowang - opened
如题
我们已经release了1.0版本的蒸馏量化模型。8step推理,H800上端到端4.5s,显存30GB。
蒸馏Lora在这里:https://huggingface.co/FireRedTeam/FireRed-Image-Edit-1.0-Lightning
我们新增了很多feature,欢迎试用:



