seait
SEAIT is a user-friendly application that simplifies the installation process of AI-related projects (by diStyApps)
kohya_ss
By bmaltais
seait | kohya_ss | |
---|---|---|
14 | 132 | |
681 | 8,414 | |
- | - | |
6.9 | 9.9 | |
8 months ago | 3 days ago | |
Python | Python | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
seait
Posts with mentions or reviews of seait.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-31.
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How to plan A1111 upgrade on Windows and keep CUDA working
install the recommended python and git from windows store and try from here to install automatic1111 from here https://github.com/diStyApps/seait its a gui and very simple just one click do install it will create a new separate venv just make sure your python is version is updated
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FaceSwap Suite Preview
Initial release will be public. and for easier installation it also be available trough https://github.com/diStyApps/seait
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Does anyone know how to install Stable Diffusion. I’ve done the process so many times and I always get this and not the running link?
use https://github.com/diStyApps/seait/releases/download/0.1.4/seait_installers_version_0.1.4.zip
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What are hidden tricks you discovered that tutorials never really cover?
If you are on windows, you could just do a second install with SEAiT.
- Take Control of Your Storage: 'SEAIT' - Offers Symlink Creation & AI Model Organization
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Vladmantic and Anapnoe collaborating on the best UI-UX for stable diffusion ever
Try this...https://github.com/diStyApps/seait
- I hope that by A1111 is everything fine. Best wishes for great man! In mean time lets, develope Vlad fork
- Super Easy AI Installer Tool (SEAIT) Update 0.1.0
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Vladmandic vs AUTOMATIC1111. Vlad's UI is almost 2x faster
seait is a life saver now
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Need help installing Stable Diffusion, please!
maybe try seait? https://github.com/diStyApps/seait is like for people who don't really know deep about installing stable diffusion, here is the video about it https://www.youtube.com/watch?v=_PJe_gSZn7I
kohya_ss
Posts with mentions or reviews of kohya_ss.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-06.
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Some semi-advanced LoRA & kohya_ss questions
Many of the options are explained here https://github.com/bmaltais/kohya_ss/wiki/LoRA-training-parameters
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Lora training with Kohya issue
training in BF16 might solve this issue from what I saw in this ticket. I know other people ran into the issue too https://github.com/bmaltais/kohya_ss/issues/1382
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What is the best way to merge multiple loras in to one model?
for lycoris loras you can use the command-line script from the kohya-ss repo https://github.com/bmaltais/kohya_ss/blob/master/networks/merge_lora.py i have an older version checked out from late july, it had a separate merge_lycoris.py for for this purpose, it's probably unified now in a single file
- Evidence that LoRA extraction in Kohya is broken?
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Merging Lora with Checkpoint Model?
I usually do that with kohya_ss, a tool made for making LoRAs and finetunes. It might be a bit of a pain to set up just to do this one task, but if nobody gives you an easier method, look into it. https://github.com/bmaltais/kohya_ss
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How I got Kohya_SS working on Arch Linux, including an up-to-date pip requirements file
After that, make your staging directory, and do the git clone https://github.com/bmaltais/kohya_ss.git, and navigate inside of it. Now, here's where things can become a pain. I used pyenv to set my system level python to 3.10.6 with pyenv global 3.10.6, though you can probably just use "local" and do it for the current shell. You NEED it to be active however before you set up your venv. If you do python --version and get 3.10.6, you're ready for this next part. Make your venv with python -m venv venv. This is the simplest way, it'll create a virtual environment in your current folder named venv. You'll do a source venv/bin/activate and then do which python to make sure it's using the python from the venv. Now for the fun part. The included setup scripts have been flaky for me, so I just went through the requirements and installed everything by hand. I'm going to do this guide right now for nvidia, because I just got a 4090 for this stuff. If this ends up working well for others and there's demand, I'll try to reproduce this for AMD (But I'll be honest, I got an nvidia card because bitsandbytes doesn't have full rocm support, nor do most libraries, so it's not very reliable). After installing everything and testing it works at least at a basic level for dreambooth training, my finished requirements.txt for pip is as below:
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The best open source LoRA model training tools
Earlier I created a post where I asked for recommendations for LoRA model training tutorials. The first one I looked at used the kohya_ss GUI. That GitHub repo already has two tutorials, which are quite good, so I ended up using those:
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Script does...nothing
I have tried my best to research this issue and have not come up with much. It is obvious that its a backend issue right? The guides that I used https://github.com/bmaltais/kohya_ss and https://github.com/pyenv-win/pyenv-win/
- Using LoRa on SDXL 1.0 (not using the Kohra GUIs)
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How do I reduce the size of my Lora models?
I am training on a 12GB 3060 using kohya_ss. Is there a setting or something I'm missing?
What are some alternatives?
When comparing seait and kohya_ss you can also consider the following projects:
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
sd_dreambooth_extension
stable-diffusion-webui-directml - Stable Diffusion web UI
EveryDream-trainer - General fine tuning for Stable Diffusion
sd-webui-controlnet - WebUI extension for ControlNet
sd-scripts
stable-diffusion-webui-ux - Stable Diffusion web UI UX
stable-diffusion-webui-model-toolkit - A Multipurpose toolkit for managing, editing and creating models.
kohya_ss_colab - a (successful) attepmt to port kohya_ss to colab
canvas-zoom - zoom and pan functionality
LoRA_Easy_Training_Scripts - A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy
seait vs automatic
kohya_ss vs sd_dreambooth_extension
seait vs stable-diffusion-webui-directml
kohya_ss vs EveryDream-trainer
seait vs sd-webui-controlnet
kohya_ss vs sd-scripts
seait vs stable-diffusion-webui-ux
kohya_ss vs automatic
seait vs stable-diffusion-webui-model-toolkit
kohya_ss vs kohya_ss_colab
seait vs canvas-zoom
kohya_ss vs LoRA_Easy_Training_Scripts