BooruDatasetTagManager
kohya_ss
BooruDatasetTagManager | kohya_ss | |
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6 | 132 | |
1,228 | 8,414 | |
- | - | |
8.9 | 9.9 | |
13 days ago | 9 days ago | |
C# | Python | |
MIT License | Apache License 2.0 |
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BooruDatasetTagManager
- CLIP and DeepDanbooru Alternatives For Prompt Generation [Relevant Self-Promotion]
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Using hydrus for managing tags of training data
There are few tools for mass tagging data. Each with their own problems. * stable-diffusion-webui-dataset-tag-editor has good features. But it also has bugs that make it nearly unusable. It is also resource heavy as it runs in the webUI with stable diffusion, and stable diffusion always has models loaded. * BooruDatasetTagManager lacks many useful features.
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just click what you want to learn
This is what I use for managing booru tags: starik222/BooruDatasetTagManager (github.com)
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What program to use for mass editing tags for training images?
BooruDatasetTagManager is another option but it has much fewer features than the above tool. For example it doesn't seem to have negative search option (show images that do not have specified tag).
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Easy way to bulk edit captions
I use Booru Dataset Tag Manager
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Captioning Datasets for Training Purposes
You’ve got a dataset. You’ve decided on a structure. You’re ready to start captioning. Now it’s time for the magic part of the workflow: BooruDatasetTagManager (BDTM). This handy piece of software will do two extremely important things for us which greatly speeds up the workflow:
kohya_ss
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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?
stable-diffusion-webui-dataset-tag-editor - Extension to edit dataset captions for SD web UI by AUTOMATIC1111
sd_dreambooth_extension
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI
EveryDream-trainer - General fine tuning for Stable Diffusion
minigpt4-batch - Use miniGPT-4 batch to generate captions for a lot of images! You should be able to create the best captions you always wanted!
sd-scripts
stable-diffusion-webui - Stable Diffusion web UI
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
MiniGPT-4 - Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
kohya_ss_colab - a (successful) attepmt to port kohya_ss to colab
sd-webui-lobe-theme - 🅰️ Lobe theme - The modern theme for stable diffusion webui, exquisite interface design, highly customizable UI, and efficiency boosting features.
LoRA_Easy_Training_Scripts - A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy