sd-scripts
By kohya-ss
pyenv
Simple Python version management (by pyenv)
sd-scripts | pyenv | |
---|---|---|
64 | 261 | |
4,253 | 37,063 | |
- | 2.2% | |
9.7 | 8.9 | |
2 days ago | 10 days ago | |
Python | Roff | |
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.
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
pyenv
Posts with mentions or reviews of pyenv.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-27.
-
Install Asdf: One Runtime Manager to Rule All Dev Environments
If you have a requirement for multiple, specific Python versions, why not just use pyenv?
https://github.com/pyenv/pyenv
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Setup and Use Pyenv in Python Applications
For more information visit: pyenv repository
- Pyenv – lets you easily switch between multiple versions of Python
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How to Create Virtual Environments in Python
Note that virtual environments assume you are using the same global version of Python. Often, this is not the case and additional tools like pyenv can be used alongside virtual environments when you need to switch between versions of Python itself on your local machine.
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How to debug Django inside a Docker container with VSCode
Python version manager pyenv
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Integrating GPT in Your Project: Create an API for Anything Using LangChain and FastAPI
First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.
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Manage your Python Project End-to-End with PDM
Note: Most modern systems will probably have a system environment that meets this requirement, but if yours does not or if you prefer not to install anything in your system environment (even if it's just PDM) check out asdf or pyenv to help install and manage additional Python environments.
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Introducing Flama for Robust Machine Learning APIs
When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage you to learn more about venv, pyenv or conda for a better understanding on how to create and manage virtual environments.
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Is KDE Desktop really snappier than XFCE these days as claimed?
For Python, with your use case I would avoid system packages, no matter the distro. It sounds like it would be worth setting up pyenv and working exclusively with virtual environments.
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Python Versions and Release Cycles
For OSX there is homebrew or pyenv (pyenv is another solution on Linux). As pyenv compiles from source it will require setting up XCode (the Apple IDE) tools to support this which can be pretty bulky. Windows users have chocolatey but the issue there is it works off the binaries. That means it won't have the latest security release available since those are source only. Conda is also another solution which can be picked up by Visual Studio Code as available versions of Python making development easier. In the end it might be best to consider using WSL on Windows for installing a Linux version and using that instead.
What are some alternatives?
When comparing sd-scripts and pyenv you can also consider the following projects:
kohya_ss
Poetry - Python packaging and dependency management made easy
sd_dreambooth_extension
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
Pipenv - Python Development Workflow for Humans.
bitsandbytes-rocm
miniforge - A conda-forge distribution.
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
virtualenv - Virtual Python Environment builder
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
Pew - A tool to manage multiple virtual environments written in pure python