Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
FluxKontextPipeline
image-generation
flux
Instructions to use AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_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("AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_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] - Diffusion Single File
How to use AlekseyCalvin/Flux_Kontext_Dev_fp8_scaled_diffusers with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle

- Xet hash:
- c0a8af1e705fb02419cb839e5ddd1ba4978b2fc779912a6cf65d36f291ed81d7
- Size of remote file:
- 1.92 MB
- SHA256:
- 1b4bc575a458fbfe83d48846748dffa51c346a54f5235ac8958961b8a61f8ecc
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