Instructions to use xinsir/controlnet-union-sdxl-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xinsir/controlnet-union-sdxl-1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xinsir/controlnet-union-sdxl-1.0", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Does the prompt you used to Training affect your reasoning using Controlnet?
#44
by Pupba - opened
I used diffusers base code to fine-tun the SDXL-ControlNet.
At this time, I tried the prompts of about 500 data sets the same and tried differently, but the results did not change significantly.
I'm going to prepare more datasets this time, but will the prompt detailing the images greatly affect the image creation that I target?
Also, does using prompts used to train ControlNet for inference greatly affect the outcome?