Instructions to use satani/500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use satani/500 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("XpucT/Deliberate", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("satani/500") prompt = "a pencil sketch in style02_V21_768_set05B style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA DreamBooth - satani/500
These are LoRA adaption weights for XpucT/Deliberate. The weights were trained on a pencil sketch in style02_V21_768_set05B style using DreamBooth. You can find some example images in the following.
- Downloads last month
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Model tree for satani/500
Base model
XpucT/Deliberate


