Instructions to use Regulus0725/random_mask_brushnet_ckpt_sdxl_regulus_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Regulus0725/random_mask_brushnet_ckpt_sdxl_regulus_v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Regulus0725/random_mask_brushnet_ckpt_sdxl_regulus_v1", 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
This is a random mask brushNet SDXL version model by Regulus, trained 1880000 steps with batch size 32.
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