yibolu
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README.md
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- art
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- Stable Diffusion
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---
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## Model Card for
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-
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Among its main features are:
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|model|time cost(ms)|
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|torch2.0.1 + diffusers|~930ms|
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## Model Sources
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```bash
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docker pull nvcr.io/nvidia/pytorch:23.02-py3
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docker run --rm -it --gpus all -v ./:/
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pip install -r requirements.txt
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python txt2img_demo.py
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## Citation
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``` bibtex
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@Misc{
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author = {Kangjian Wu, Zhengtao Wang, Yibo Lu, Haoxiong Su, Bin Wu},
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title = {
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howpublished = {\url{https://huggingface.co/TMElyralab/
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year = {2023}
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}
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```
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## Report bug
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- start a discussion to report any bugs!--> https://huggingface.co/TMElyralab/
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- report bug with a `[bug]` mark in the title.
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- art
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- Stable Diffusion
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---
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## Model Card for lyraSD
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lyraSD is currently the **fastest Stable Diffusion model** that can 100% align the outputs of **diffusers** available, boasting an inference cost of only **0.52 seconds** for a 512x512 image, accelerating the process up to **80% faster** than the original version.
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Among its main features are:
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|model|time cost(ms)|
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|:-:|:-:|
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|torch2.0.1 + diffusers|~930ms|
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|lyraSD|~745ms|
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## Model Sources
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```bash
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docker pull nvcr.io/nvidia/pytorch:23.02-py3
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docker run --rm -it --gpus all -v ./:/lyraSD nvcr.io/nvidia/pytorch:23.02-py3
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pip install -r requirements.txt
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python txt2img_demo.py
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## Citation
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``` bibtex
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@Misc{lyraSD_2023,
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author = {Kangjian Wu, Zhengtao Wang, Yibo Lu, Haoxiong Su, Bin Wu},
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title = {lyraSD: Accelerating Stable Diffusion with best flexibility},
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howpublished = {\url{https://huggingface.co/TMElyralab/lyraSD}},
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year = {2023}
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}
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```
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## Report bug
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- start a discussion to report any bugs!--> https://huggingface.co/TMElyralab/lyraSD/discussions
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- report bug with a `[bug]` mark in the title.
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