Instructions to use diffusers/controlnet-depth-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/controlnet-depth-sdxl-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("diffusers/controlnet-depth-sdxl-1.0") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Hyperparameters and steps to sudden convergence
#9
by brycegoh - opened
Hi Diffuser team, I am attempting to train my own controlnet and was wondering if your team has any tips for training a sdxl controlnet?
Given that your team seem to use a different script from the documented one, it seems like you use the EDM formulation.
Would appreciate opinions on:
- How does the EDM formulation help the training process training?
- What hyperparameters did your team use (I see that batch size and LR is documented but what about gradient accumulation, etc)?
- Did your team notice any patterns for sudden convergence?