Instructions to use stepfun-ai/Step1X-Edit-v1p1-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stepfun-ai/Step1X-Edit-v1p1-diffusers 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("stepfun-ai/Step1X-Edit-v1p1-diffusers", 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] - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 6f004327c4d8291d0de3a8784fdad445c9f977000b1540237081cce57bb0f658
- Size of remote file:
- 442 kB
- SHA256:
- 9b6a31f9e9f6ad060e4b537bc28b45e583f6e3f6aa08a867f59c733aa00fabf0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.