Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
Flux2KleinPipeline
text-to-image
image-editing
flux
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("xcreates/FLUX.2-klein-4B", 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]See FLUX.2-klein-4B in action - demonstration video
Usage Notes
Tested using xCreate app v1.1.1
- M3 Ultra: ~9.7 seconds for a generation
- M4 Max: ~17.8 seconds for a generation
- M1 Max: ~56 seconds for a generation
- Memory usage: ~28 GB
For more details see demonstration video or visit black-forest-labs/FLUX.2-klein-4B.
Disclaimer
We are not the creator, originator, or owner of any model listed. Each model is created and provided by third parties. Models may not always be accurate or contextually appropriate. You are responsible for verifying the information before making important decisions. We are not liable for any damages, losses, or issues arising from its use, including data loss or inaccuracies in AI-generated content.
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