kohya_ss
By bmaltais
sd-scripts
By kohya-ss
kohya_ss | sd-scripts | |
---|---|---|
132 | 64 | |
8,362 | 4,222 | |
- | - | |
9.9 | 9.7 | |
5 days ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | 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.
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?
sd-scripts
Posts with mentions or reviews of sd-scripts.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-11-16.
- Everything you know about loss is a lie
- Evidence that LoRA extraction in Kohya is broken?
- Stable Diffusion XL (SDXL) DreamBooth training with EMA (Exponential Moving Average) on the way
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Installing kohya_ss GUI on AWS
This repository mostly provides a Windows-focused Gradio GUI for Kohya's Stable Diffusion trainers... but support for Linux OS is also provided through community contributions.
- Question on SD Finetuning
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Trying to put up a simple dreambooth for sdxl, but an errors pops up
Leaving this here because i'm very tired, so this is the file of the ipynb that uses the sdxl_train.py from the https://github.com/kohya-ss/sd-scripts/tree/sdxl repo, if anybody find out why when getting to the training i get this very empty error : " [00:09:11] WARNING The following values were not passed to "
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Finally SDXL coming to the Automatic1111 Web UI
You can try and test training LoRAs now https://github.com/kohya-ss/sd-scripts/tree/sdxl
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Help with LORA Training - Kohya_ss Regularization
This might help.
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need a lora traning guide for linux
Kohya_ss sd-scripts Seems to be the standard for lora training. The linked page has an English translation, but doesn't really have system specific tips. Someone else has a popular gui for it, but it's designed with windows in mind. There's another, simpler gui, but its still in development and the dev doesn't do any testing on Linux. With any of these, I run into dependency conflicts like crazy.
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SDXL 0.9 is wild but trying to imagine where we go from here is breaking my brain.
"Direct training" is already feasible with masking in kohya-ss: https://github.com/kohya-ss/sd-scripts/pull/589
What are some alternatives?
When comparing kohya_ss and sd-scripts you can also consider the following projects:
sd_dreambooth_extension
EveryDream-trainer - General fine tuning for Stable Diffusion
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
bitsandbytes-rocm
kohya_ss_colab - a (successful) attepmt to port kohya_ss to colab
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
LoRA_Easy_Training_Scripts - A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
sd-webui-additional-networks
EveryDream2trainer
kohya_ss vs sd_dreambooth_extension
sd-scripts vs sd_dreambooth_extension
kohya_ss vs EveryDream-trainer
sd-scripts vs ComfyUI
kohya_ss vs automatic
sd-scripts vs bitsandbytes-rocm
kohya_ss vs kohya_ss_colab
sd-scripts vs lora
kohya_ss vs LoRA_Easy_Training_Scripts
sd-scripts vs kohya-trainer
kohya_ss vs sd-webui-additional-networks
sd-scripts vs EveryDream2trainer