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
Why is generated image noisy?
I apologize. I must have screwed up the scaled weight conversion in this instance. It was bugging out for me as well (though I wasn't sure if it was just me). But it seems I was negligent to have kept this repo up, especially without warning. For training, at least if you're using AI-toolkit, I would highly suggest this hqq/nf4 conversion of Kontext at https://huggingface.co/HighCWu/FLUX.1-Kontext-dev-bnb-hqq-4bit for faster/lower-VRAM training (which also enables training at higher resolutions if you do have more VRAM for training: highly recommended for Kontext). This 4bit will definitely work for training with HighCWu's fork at https://github.com/HighCWu/ai-toolkit or my fork at https://github.com/AlekseyCalvin/ai-toolkit-soonr .
For inference, I've just kept using https://huggingface.co/buildborderless/FLUX.1_Kontext-Lightning-8step
