Instructions to use maple-research-lab/SIM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maple-research-lab/SIM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maple-research-lab/SIM", 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 Settings
- Draw Things
- DiffusionBee
metadata
license: agpl-3.0
datasets:
- PixArt-alpha/SAM-LLaVA-Captions10M
language:
- en
base_model:
- PixArt-alpha/PixArt-alpha
pipeline_tag: text-to-image
library_name: diffusers
tags:
- diffusion
- distillation
SIM: One-Step Diffusion Distillation through Score Implicit Matching
π Quick Start
please refer to https://github.com/maple-research-lab/SIM for the inference code. We are working on the integration into diffusers.
π Citation
@article{luo2024one,
title={One-Step Diffusion Distillation through Score Implicit Matching},
author={Luo, Weijian and Huang, Zemin and Geng, Zhengyang and Kolter, J Zico and Qi, Guo-jun},
journal={arXiv preprint arXiv:2410.16794},
year={2024}
}
