Image-to-Image
Diffusers
Safetensors
ControlNetModel
StableDiffusionXLControlNetInpaintPipeline
ControlNetModel
stable-diffusion-xl
inpainting
light-estimation
relighting
Instructions to use pureexe/chromeball-sdxl-ev0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pureexe/chromeball-sdxl-ev0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("pureexe/chromeball-sdxl-ev0", dtype=torch.bfloat16, device_map="cuda") prompt = "a perfect mirrored reflective chrome ball sphere" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
could you point me in the right direction?
#1
by kagevazquez - opened
What repo are you using for SDXL ControlNet training?
I'm using code from Diffusers
See https://github.com/huggingface/diffusers/blob/main/examples/controlnet/train_controlnet_sdxl.py