Text-to-Image
Diffusers
stable-diffusion
stable-diffusion-diffusers
controlnet
control-lora-v3
diffusers-training
Instructions to use HighCWu/control-lora-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HighCWu/control-lora-v3 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("HighCWu/control-lora-v3") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Ctrl+K
- imgs
- sd-control-lora-v3-canny-half_skip_attn-rank16-conv_in-rank64
- sd-control-lora-v3-depth-half-rank8-conv_in-rank128
- sd-control-lora-v3-normal-half-rank32-conv_in-rank128
- sd-control-lora-v3-pose-half-rank128-conv_in-rank128
- sd-control-lora-v3-segmentation-half_skip_attn-rank128-conv_in-rank128
- sd-control-lora-v3-tile-half_skip_attn-rank16-conv_in-rank64
- sdxl-control-lora-v3-canny-half_skip_attn-rank16-conv_in-rank64
- 4.52 kB
- 7.71 kB