Flux Controlnet Hed Diffusers

🚀 FLUX.1-dev Hed ControlNet Diffusers Version

This repository offers a Diffusers version of the FLUX.1-dev Hed ControlNet checkpoint by Xlabs AI, enabling text - to - image generation.

🚀 Quick Start

This model can be used directly with the diffusers library. Here is a step - by - step guide on how to use it:

💻 Usage Examples

Basic Usage

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-hed-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-hed-diffusers/resolve/main/hed_example.png")
prompt = "photo of woman in the cyberpank city"

image = pipe(
    prompt,
    control_image=control_image,
    controlnet_conditioning_scale=0.7,
    num_inference_steps=25,
    guidance_scale=3.5,
    height=1376,
    width=1024,
    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.

🔍 Model Information

The original repo can be found here.