kohya_ss
By bmaltais
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sd_dreambooth_extension | kohya_ss | |
---|---|---|
115 | 132 | |
1,818 | 8,248 | |
- | - | |
9.0 | 9.8 | |
about 1 month ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | 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.
sd_dreambooth_extension
Posts with mentions or reviews of sd_dreambooth_extension.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-06.
- SDXL Training for Auto1111 is now Working on a 24GB Card
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(Requesting Help)
I am trying to use StableDiffusion via AUTOMATIC1111 with the Dreambooth extension
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it will be an absolute madness when sdxl becomes standard model and we start getting other models from it
When I first attempted SD training, I was very frustrated. It wasn't until I found this obscure forum thread on Github that I actually started producing great results with Dreambooth. Because I have such satisfactory results, I'm very reluctant to beat my brains against LoRa and its related training techniques. I gave up trying to train TI embeddings a long time ago. And I never figured out how to train or how to use hypernetworks. I've only been able to get good results with Dreambooth directly because of that thread I linked above. I make LoRas by extracting them from Dreambooth-trained checkpoints. And I have no idea if I'm doing the extractions the right way or not.
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"Exception training model: ' Some tensors share memory" with Dreambooth on Vladmatic
Getting the same with automatic1111 and sd_dreambooth extension. Check out more here in the issues log: https://github.com/d8ahazard/sd_dreambooth_extension/issues/1266
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Yo, DreamBooth gatekeepers, SHARE YOUR HYPERPARAMETERS, please.
It's several moths old and many things have changed. But the spreadsheet available through this thread on Github has been indispensable for me when I train Dreambooth models. I'm astounded no one talks about it. I bring it up all the time. The research presented there should be continued. I'd love to see similar research done for SD v2.1.
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What is the BEST solution for hyper realistic person training?
Training rate is paramount. Read this Github thread.
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How do you train your LoRAs, 1 Epoch or >1 Epoch (same # of steps)?
https://github.com/d8ahazard/sd_dreambooth_extension/discussions/547/ (in depth training principles understanding)
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Struggling to install Dreambooth
sd_dreambooth_extension https://github.com/d8ahazard/sd_dreambooth_extension.git main 926ae204 Fri Mar 31 15:12:45 2023 unknown
- Attempting to train a lora with RTX 2060 6 GB vRAM, how to go about this?
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SD just released an open source version of their GUI called StableStudio
also the Dreambooth extension supports API (https://github.com/d8ahazard/sd_dreambooth_extension/blob/main/scripts/api.py) so i'm not sure where do you get those news :/
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 sd_dreambooth_extension and kohya_ss you can also consider the following projects:
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
EveryDream-trainer - General fine tuning for Stable Diffusion
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
sd-scripts
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
dreambooth-training-guide
kohya_ss_colab - a (successful) attepmt to port kohya_ss to colab
LoRA_Easy_Training_Scripts - A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy
sd-webui-controlnet - WebUI extension for ControlNet
sd-webui-additional-networks
sd_dreambooth_extension vs lora
kohya_ss vs EveryDream-trainer
sd_dreambooth_extension vs kohya-trainer
kohya_ss vs sd-scripts
sd_dreambooth_extension vs stable-diffusion-webui-wd14-tagger
kohya_ss vs automatic
sd_dreambooth_extension vs dreambooth-training-guide
kohya_ss vs kohya_ss_colab
sd_dreambooth_extension vs sd-scripts
kohya_ss vs LoRA_Easy_Training_Scripts
sd_dreambooth_extension vs sd-webui-controlnet
kohya_ss vs sd-webui-additional-networks