Instructions to use pskl/icondiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pskl/icondiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("pskl/icondiffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "asim style, a tree, centered, monochrome, line-art, logo" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("pskl/icondiffusion", dtype=torch.bfloat16, device_map="cuda")
prompt = "asim style, a tree, centered, monochrome, line-art, logo"
image = pipe(prompt).images[0]SD Offset noise 1.5 finetuned on 512x512 svgs.
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