Instructions to use songkey/hm_reference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use songkey/hm_reference with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("songkey/hm_reference", 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
File size: 972 Bytes
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library_name: diffusers
license: mit
base_model:
- stable-diffusion-v1-5/stable-diffusion-v1-5
---
Model of [**HelloMeme**](https://songkey.github.io/hellomeme/)
[**Project Page**](https://songkey.github.io/hellomeme/) | [**Code Page**](https://github.com/HelloVision/HelloMeme) | [**Arxiv**](https://arxiv.org/abs/2410.22901) | [**ComfyUI**](https://github.com/HelloVision/ComfyUI_HelloMeme) | [**Demo**](https://www.modelscope.cn/studios/songkey/HelloMeme)
**BibTeX:**
```bibtex
@misc{zhang2024hellomemeintegratingspatialknitting,
title={HelloMeme: Integrating Spatial Knitting Attentions to Embed High-Level and Fidelity-Rich Conditions in Diffusion Models},
author={Shengkai Zhang and Nianhong Jiao and Tian Li and Chaojie Yang and Chenhui Xue and Boya Niu and Jun Gao},
year={2024},
eprint={2410.22901},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2410.22901},
}
```
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