Instructions to use peteromallet/Flux-Kontext-InScene with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use peteromallet/Flux-Kontext-InScene 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("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("peteromallet/Flux-Kontext-InScene") 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
- Local Apps Settings
- Draw Things
Download samples.png from peteromallet/Flux-Kontext-InScene: direct link, hf CLI and curl.
- Browser
- Download file 5.81 MB
-
https://huggingface.co/peteromallet/Flux-Kontext-InScene/resolve/main/samples.png
- Command line
-
hf download hf://peteromallet/Flux-Kontext-InScene/samples.png
-
curl -L -o samples.png https://huggingface.co/peteromallet/Flux-Kontext-InScene/resolve/main/samples.png
5.81 MB

- Xet hash:
- 487c76f3f6800f1c0d45b86762b4ae42e2b9865a7915b7a8db91eed92aa1ef95
- Size of remote file:
- 5.81 MB
- SHA256:
- 6265eda59fb69bd5edb28884ca30e5a89884039086ef66c041e1a7409bf71802
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.