Instructions to use kasukanra/linebrush-style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kasukanra/linebrush-style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kasukanra/linebrush-style", 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
- Draw Things
- DiffusionBee
This is a fine-tuned Stable Diffusion model (v1.5) trained on images with an ink brush or heavy lineart style from various fantasy concept illustrators and designers. Use the tokens DBlinebrush style in your prompts for the effect.
Download the checkpoint file (.ckpt) to use it.
If you want to reproduce the images below, I've prepared a more detailed version of the prompt settings and seed values in this Github Gist: https://gist.github.com/kudou-reira/eadf52cef156eb566cff886221823748
Example settings: Steps: 50, Sampler: Euler, CFG scale: 7, Size: 512x512
Example prompt: DBlinebrush style, masterpiece, 1girl, beautiful portrait of an anime female adventurer, monochrome
Some example images in txt2img (very minimal editing/cleanup):
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