To run

Check out sayakpaul/flux.1-dev-nf4-pkg that shows how to run this checkpoint along with an NF4 T5 in a free-tier Colab Notebook.

Be mindful of the license of Flux.1-Dev here.

Make sure you have the latest versions of bitsandbytes and accelerate installed.

And then install diffusers from this PR:

pip install git+https://github.com/huggingface/diffusers@c795c82df39620e2576ccda765b6e67e849c36e7
import torch
from diffusers import FluxTransformer2DModel, FluxPipeline

model_id = "black-forest-labs/FLUX.1-dev"
nf4_id = "sayakpaul/flux.1-dev-nf4-with-bnb-integration"
model_nf4 = FluxTransformer2DModel.from_pretrained(nf4_id, torch_dtype=torch.bfloat16)
print(model_nf4.dtype)
print(model_nf4.config.quantization_config)

pipe = FluxPipeline.from_pretrained(model_id, transformer=model_nf4, torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload()

prompt = "A mystic cat with a sign that says hello world!"
image = pipe(prompt, guidance_scale=3.5, num_inference_steps=50, generator=torch.manual_seed(0)).images[0]
image.save("flux-nf4-dev-loaded.png")

image/png

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