import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("SamuelTallet/FLUX.2-klein-4B-SDNQ-8bit-dynamic-hadamard256", 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]This is FLUX.2 [klein] 4B optimized using SDNQ with INT8 dynamic quantization and Hadamard Rotation (Group size: 256).
Sample
Prompt:
A cat holding a sign that says hello world
Seed: 922520
Usage
Install Torch, Diffusers (Git), SDNQ 0.2.0 and Triton.
Use CFG 1 and 4 steps.
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black-forest-labs/FLUX.2-klein-4B