alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha版本v1.0 (ID: 875901)

This repository provides a Inpainting ControlNet checkpoint for FLUX.1-dev model released by AlimamaCreative Team.

News

? Thanks to @comfyanonymous，ComfyUI now supports inference for Alimama inpainting ControlNet. Workflow can be downloaded from here.

ComfyUI Usage Tips:

• Using the t5xxl-FP16 and flux1-dev-fp8 models for 28-step inference, the GPU memory usage is 27GB. The inference time with cfg=3.5 is 27 seconds, while without cfg=1 it is 15 seconds. Hyper-FLUX-lora can be used to accelerate inference.

• You can try adjusting（lower） the parameters control-strength, control-end-percent, and cfg to achieve better results.

• The following example uses control-strength = 0.9 & control-end-percent = 1.0 & cfg = 3.5

InputOutputPromptModel Cards

• The model was trained on 12M laion2B and internal source images at resolution 768x768. The inference performs best at this size, with other sizes yielding suboptimal results.

• The recommended controlnet_conditioning_scale is 0.9 - 0.95.

• Please note: This is only the alpha version during the training process. We will release an updated version when we feel ready.

pip install diffusers==0.30.2

git clone https://github.com/alimama-creative/FLUX-Controlnet-Inpainting.git

python main.py