LyCORIS
Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion. (by KohakuBlueleaf)
LoRA_Easy_Training_Scripts
A UI made in Pyside6 to make training LoRA/LoCon and other LoRA type models in sd-scripts easy (by derrian-distro)
LyCORIS | LoRA_Easy_Training_Scripts | |
---|---|---|
13 | 14 | |
1,983 | 938 | |
- | - | |
9.6 | 7.7 | |
8 days ago | 18 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 only |
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.
LyCORIS
Posts with mentions or reviews of LyCORIS.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-28.
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LoRA (LyCORIS) iA3 is amazing (info in 1st comment)
Lycoris is another implementation of LoRA done by KohakuBlueleaf: https://github.com/KohakuBlueleaf/LyCORIS
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Training LORAs locally guide in text form?
Most guides focus on LoRa training as that has been around for longer. But I think LoHa can give better results. But the training is about half as fas it/s and it requires different training settings.
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Guide to DreamBooth / LORA / LyCORIS
I've read in some tutorials that it is best that the value should be 64 or below, also here they suggest to not go over 64 ( https://github.com/KohakuBlueleaf/LyCORIS )
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LyCORIS doesn't work with inpainting models
Does anyone know how to make LyCORIS models (https://github.com/KohakuBlueleaf/LyCORIS) work with inpainting models?
- wtf is a lycoris?
- I wonder what to do with this?
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I'm the creator of LoRA. How can I make it better?
I think it was linked already but this is also relevant for LoRa: https://github.com/KohakuBlueleaf/LyCORIS Nice work!
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LoRA: Low-Rank Adaptation of Large Language Models
There are some WIP evolutions of SD Lora in the works, like locon and lycoris.
https://github.com/KohakuBlueleaf/LyCORIS
- What the hell is a Locon/Loha model?
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SD fine-tuning methods compared: a benchmark
You might want to expand LoRA to include LoCon and LoHa, (and also add a column for VRAM requirements) (Think of it as a more complete LoRA that works for the kernels in the convolutional units rather than just the weights for the feed-forward network), support is still quite limited, but it's starting to pick up steam https://github.com/KohakuBlueleaf/LyCORIS
LoRA_Easy_Training_Scripts
Posts with mentions or reviews of LoRA_Easy_Training_Scripts.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-02.
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Could anyone please help with getting these scripts to work in Google Colab or Kaggle?
Hello! I want to run these scripts in Google Colab (https://github.com/derrian-distro/LoRA_Easy_Training_Scripts), but I don't know how. Tried to replace some code in this Colab (https://colab.research.google.com/github/camenduru/kohya_ss-colab/blob/main/kohya_ss_colab.ipynb), but it didn't go anywhere, so that's why I'm asking about it here. Could anyone help with this problem of mine please? I can clone git content, but I don't know how to run needed .bat or .sh file there.
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need a lora traning guide for linux
conda create -n lora-easy-ui python=3.10.6 conda activate lora-easy-ui git clone https://github.com/derrian-distro/LoRA_Easy_Training_Scripts cd LoRA_Easy_Training_Scripts conda install -c anaconda cudatoolkit git submodule init git submodule update cd sd_scripts python -m venv venv source venv/bin/activate pip3 install torch torchvision torchaudio pip install -r requirements.txt pip install xformers pip install -r ../requirements_ui.txt pip install ../LyCORIS/. accelerate config
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Has anyone had any luck getting kohya scripts installed and running on Ubuntu (or Linux in genera)?
I use this https://github.com/derrian-distro/LoRA_Easy_Training_Scripts on Kubuntu. It works very well.
- Kohya stopped working closes immediately after opening
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help to create a lora in stable diffusion
The same thing happened to me, I could never run it well, but thanks to that I met easy lora, it has a very intuitive interface, it installs very clean, and it works impeccable, it doesn't change almost all of the configuration, just choose the model, your photos and the epocs or steps, and it works great https://github.com/derrian-distro/LoRA_Easy_Training_Scripts
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Can't Get Any LoRA Training Repos To Work
Are there any Repos that actually work? I've attempted https://github.com/derrian-distro/LoRA_Easy_Training_Scripts, as well as a few variations of the kohya_ss ones to no avail.
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Keep getting failed to match keys when loading newly trained lora.
This is my 3rd one, can someone point me to the right direction? I'm using https://github.com/derrian-distro/LoRA_Easy_Training_Scripts/releases/tag/installers-v5
- keep getting "failed to match keys error when loading my self trained lora"
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Have you got running LoRA training on an AMD GPU?
Then, git clone https://github.com/derrian-distro/LoRA_Easy_Training_Scripts
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LoRA training issue
I'm attempting to train a LoRA using Kohya's SD Scripts and one of Derrian's LoRA Easy Training Scripts (the popup version). I've been able to set everything up fine, boot up the venv, run the script, get everything spinning, etc. until:
What are some alternatives?
When comparing LyCORIS and LoRA_Easy_Training_Scripts you can also consider the following projects:
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
kohya_ss
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
sd-scripts
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
pyenv-virtualenv - a pyenv plugin to manage virtualenv (a.k.a. python-virtualenv)
sd-webui-additional-networks
pyenv - Simple Python version management
bitsandbytes-rocm
StableTuner - Finetuning SD in style.
civitai - A repository of models, textual inversions, and more
LyCORIS vs lora
LoRA_Easy_Training_Scripts vs kohya_ss
LyCORIS vs LoRA
LoRA_Easy_Training_Scripts vs sd-scripts
LyCORIS vs ComfyUI
LoRA_Easy_Training_Scripts vs pyenv-virtualenv
LyCORIS vs sd-webui-additional-networks
LoRA_Easy_Training_Scripts vs pyenv
LyCORIS vs kohya_ss
LoRA_Easy_Training_Scripts vs bitsandbytes-rocm
LyCORIS vs StableTuner
LyCORIS vs civitai