Instructions to use satani/600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use satani/600 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/600") prompt = "a pencil sketch in style02_V21_768_set05B style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
license: creativeml-openrail-m
base_model: XpucT/Deliberate
instance_prompt: a pencil sketch in style02_V21_768_set05B style
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
inference: true
LoRA DreamBooth - satani/600
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.



