kohya-trainer
Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning (by Linaqruf)
EveryDream-trainer
General fine tuning for Stable Diffusion (by victorchall)
kohya-trainer | EveryDream-trainer | |
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36 | 32 | |
1,772 | 501 | |
- | - | |
8.3 | 2.4 | |
about 2 months ago | about 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | MIT License |
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-trainer
Posts with mentions or reviews of kohya-trainer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-04.
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Best method for training lora with sdxl
This longer colab notebook: I did use this one (or one of the slight derivatives of it) and got out a safetensors file, but the lora didn't work at all--I'd use it a increase it's weight but I just would see no effect
- Question on SD Finetuning
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Requesting Help: Stable Diffusion with Dreambooth via Automatic1111
It isn't what you are asking for (sry) but I struggled with this thing for way too long until I found out about the Kohya Trainer. https://github.com/Linaqruf/kohya-trainer So much easier with a lot of videos by the various YT folks. Standalone WebUI that just works. Life is good here!
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Do you need a PhD in AI for AI opportunities?
It's seem that he is stable diffusion model creators. In that space, it's less knowing about the code and more experimenting on what would happen in the training. The stable diffusion community has repertoire of fine-tuning tools that is accessible for someone who have no single idea on the code behind it, no different than using application like kohya.
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Am I some kind of idiot? I cant for the life of me get Lora training to work on colab or runpod.
Have you tried out one of the colabs from https://github.com/Linaqruf/kohya-trainer ? The colabs themselves are pretty long, but you just have to read each step and then usually push the button to run that cell, then move on to the next one.
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[Stable Diffusion] Diffusion stable sur Google Colab se bloque toujours!
** https: //github.com/linaqruf/kohya-trainer**
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Lora training steps with large batch sizes?
There are a lot of variables that affect what kind of settings to use, but afaik the best solution to finding the right step count for what your training is still just to save multiple epochs and then run a x/y/z plot comparison. If you can't do that locally because of your 4gb card, you could try using Lora colabs that include inference capabilities.
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Colab Troubles (Addendum)
You seem to be a little confused. You wont find an ipynb of a model. You would reference a model via a content portal like hugginface. If your model is hosted there, you dont have to download it to your computer or gdrive first. You just reference it with the hugginface-style reference, ie runwayml/stable-diffusion-v1-5. Some colabs will let you also reference a URL to pull down the model. Example. https://github.com/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb. In that case, you can get the direct url to a checkpoint, for example at civit.ai. If you're decent at messing around with code, you can deconstruct that code block to use in a different colab. As for gdrive, it's only a couple dollars to get 100G.
- PNG info not copied from images generated through Kohya.
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Is Colab going to start banning people who use it for Stable Diffusion????
Try this colab to train Lora, it can generate image without the UI too
EveryDream-trainer
Posts with mentions or reviews of EveryDream-trainer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-10.
- How should I train Dreambooth to understand a new class?
- SDTools v1.5
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Guide on finetuning a model with mid-sized dataset of family pictures
https://github.com/victorchall/EveryDream-trainer Haven't tried it myself.
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I've been collecting millions of images of only public domain /cc0 licensing. I'd like to train a stable diffusion model on the collection. Could some one share their knowledge of what this would take? Otherwise, simply enjoy my library.
In terms of training, you've got some really good links and comments to youtube tutorials, but if you're interested in more information about finetuning a model (as opposed to training from scratch), this is a good repo that has a lot of tools for finetuning, including an auto-captioner using BLIP and automatic file renaming. This is the actual finetuning repo.
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Alternative tools to fine tune stable diffusion models?
Every Dream Trainer: Is basically a Dreambooth combine with Fine Tunning, so you can train multiples thing and a lot images: https://github.com/victorchall/EveryDream-trainer
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Training with Dreambooth Models and/or Training with Automatic 1111 Textural Inversion
If you have the GPU for it, I'd recommend training all three things at once with (for example) https://github.com/victorchall/EveryDream-trainer. It recommends using "ground truth" training images - i.e. images from LAION-5B, which Stable Diffusion was originally trained with to have better prior preservation (retaining the flexibility of the original model) while incorporating new concepts, potentially even several different concepts in a single training run.
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Flexible-Diffusion. My first experiment with finetuning. A broad model with better general aesthetics and coherence for different styles! Scroll for 1.5 vs FlexibleDiffusion grids. (BTW, PublicPrompts.art is back!!!)
I used about 300 captioned images (mainly beautiful MJ stuff), and used https://github.com/victorchall/EveryDream-trainer on RunPod for finetuning
- What do you think is the right dataset size to train/refine on dreambooth?
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Practice your christmas cookies before you bake with this SD 1.5 model
SD 1.5 512x512 model for making christmas style cookies of whatever you'd like. trained on 30 512x512 images with manual captions in everydream
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Guide for train/finetune with different image sizes, not dreambooth
This is the good one: https://github.com/victorchall/EveryDream-trainer
What are some alternatives?
When comparing kohya-trainer and EveryDream-trainer you can also consider the following projects:
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
kohya_ss
sd_dreambooth_extension
StableTuner - Finetuning SD in style.
sd-webui-additional-networks
EveryDream - Advanced fine tuning tools for vision models
stable-diffusion-webui-colab - stable diffusion webui colab
EveryDream2trainer
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
stable-diffusion-webui - Stable Diffusion web UI
sd-scripts
DreamArtist-stable-diffusion - stable diffusion webui with contrastive prompt tuning
kohya-trainer vs lora
EveryDream-trainer vs kohya_ss
kohya-trainer vs sd_dreambooth_extension
EveryDream-trainer vs StableTuner
kohya-trainer vs sd-webui-additional-networks
EveryDream-trainer vs EveryDream
kohya-trainer vs stable-diffusion-webui-colab
EveryDream-trainer vs EveryDream2trainer
kohya-trainer vs fast-stable-diffusion
EveryDream-trainer vs stable-diffusion-webui
kohya-trainer vs sd-scripts
EveryDream-trainer vs DreamArtist-stable-diffusion