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Community Integration: Making AIGC cheaper, faster, and more efficient. #1212
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Hey @binmakeswell, This sounds great - I think we'd be very interested in having a better integration here! Also cc @patil-suraj @thomwolf |
This is very cool @binmakeswell ! Would be very happy to integrate diffusers in colossalAI examples! |
Thanks for your enthusiastic response and we look forward to working together! How do you expect it to be carried out? |
Hi, @patrickvonplaten and @patil-suraj , thank you for the enthusiastic response. |
Hey @binmakeswell, Should we jump on a call to discuss? :-) I think we've reached out via email |
Sure. @patrickvonplaten I just emailed(ybl@hpcaitech.com) you our available hours. Looking forward to our meeting and cooperation :-) |
This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread. Please note that issues that do not follow the contributing guidelines are likely to be ignored. |
Hopefully not stale. |
We are working in process for this integration : ) |
Any update @binmakeswell ? It would be very great to fasten training process. I found train_dreambooth.py and train_dreambooth_colossalai.py that are based on diffusers. |
Thank you for your interest and contribution to colossalai, we have merged into the hugging face diffuser library. |
This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread. Please note that issues that do not follow the contributing guidelines are likely to be ignored. |
Is there any progress? |
It's merged to |
so does that mean that integration with Automatic1111 is around the corner? |
@Sniper199999 Last I paid attention, automatic1111 isn't based on diffusers at all, so unless that has changed since I last looked, short answer is "no, probably not" |
Actually we'd really like to integrate Should we try to create a module plug-in? |
Is your feature request related to a problem? Please describe.
AIGC has recently risen to be one of the hottest topics in AI. Unfortunately, large hardware requirements and training costs are still a severe impediment to the rapid growth of the AIGC industry. The Stable Diffusion v1 version of the model requires 150,000 A100 GPU Hours for a single training session.
Describe the solution you'd like
We are happy to share a fantastic solution where the costs of training AIGC models such as stable diffusion can be 7 times cheaper!
Colossal-AI release a complete open-source Stable Diffusion pretraining and fine-tuning solution with the pretraining cost reduced by 6.5 times, and the hardware cost of fine-tuning by 7 times. An RTX 2070/3050 PC is good enough to accomplish the fine-tuning task flow, allowing AIGC models such as Stable Diffusion to be available to a wider community.
Open-source code:https://github.com/hpcaitech/ColossalAI/tree/main/examples/images/diffusion
Additional context
More details can be found on the blog. We believe the democratization of AIGC models is also very helpful for Hugging Face members. We would appreciate it if we could build the integration with you to benefit both of our users and we are willing to provide help you need in this cooperation for free.
Thank you very much.
Best regards,
Yongbin Li, HPC-AI Tech
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