Description
This repository provides a Diffusers version of FLUX.1-dev Canny ControlNet checkpoint by Xlabs AI, original repo.
How to use
This model can be used directly with the diffusers library
import torch
from diffusers.utils import load_image
from diffusers import FluxControlNetModel
from diffusers.pipelines import FluxControlNetPipeline
from PIL import Image
import numpy as np
generator = torch.Generator(device="cuda").manual_seed(87544357)
controlnet = FluxControlNetModel.from_pretrained(
"Xlabs-AI/flux-controlnet-canny-diffusers",
torch_dtype=torch.bfloat16,
use_safetensors=True,
)
pipe = FluxControlNetPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
controlnet=controlnet,
torch_dtype=torch.bfloat16
)
pipe.to("cuda")
control_image = load_image("https://huggingface.co/Xlabs-AI/flux-controlnet-canny-diffusers/resolve/main/canny_example.png")
prompt = "handsome girl with rainbow hair, anime"
image = pipe(
prompt,
control_image=control_image,
controlnet_conditioning_scale=0.7,
num_inference_steps=25,
guidance_scale=3.5,
height=1024,
width=768,
generator=generator,
num_images_per_prompt=1,
).images[0]
image.save("output_test_controlnet.png")
License
Our weights fall under the FLUX.1 [dev] Non-Commercial License
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Base model
black-forest-labs/FLUX.1-dev