Instructions to use chestnutlzj/Edit-R1-FLUX.1-Kontext-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chestnutlzj/Edit-R1-FLUX.1-Kontext-dev 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("chestnutlzj/Edit-R1-FLUX.1-Kontext-dev", 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:
- 20707762cdb712b8769d8ff27614df1b3ba9f5f28252baf578f615409399ab97
- Size of remote file:
- 209 MB
- SHA256:
- 14756b266539809eda191307aa3a950578304efecd1ec68130f4a15d6de861a8
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