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# EveryDream Trainer 2.0
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Welcome to v2.0 of EveryDream trainer! Now with more Diffusers, faster, and even more features!
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For the most up to date news and community discussions, please join us on Discord!
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[![Discord! ](.github/discord_sm.png )](https://discord.gg/nQaxwrPT)
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If you find this tool useful, please consider subscribing to the project on Patreon or a one-time donation on Ko-fi. Your donations keep this project alive as a free open source tool with ongoing enhancements.
[![Patreon ](.github/patreon-medium-button.png )](https://www.patreon.com/everydream) or [![Kofi ](.github/kofibutton_sm.png )](https://ko-fi.com/everydream).
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If you're coming from Dreambooth, please [read this ](doc/NOTDREAMBOOTH.md ) for an explanation of why EveryDream is not Dreambooth.
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## Requirements
Windows 10/11, Linux (Ubuntu 20.04+ recommended), or use the linux Docker container
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Python 3.10.x
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Nvidia GPU with 11GB VRAM or more (note: 1080 Ti and 2080 Ti may require compiling xformers yourself)
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16GB system RAM recommended minimum
Single GPU is currently supported
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32GB of system RAM recommended for 50k+ training images, but may get away with sufficient swap file and 16GB
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Ampere or newer 24GB+ (3090/A5000/4090, etc) recommended for 10k+ images
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...Or use any computer with a web browser and run on Vast/Colab. See [Cloud ](#cloud ) section below.
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## Video tutorials
### [Basic setup and getting started](https://www.youtube.com/watch?v=OgpJK8SUW3c)
Covers install, setup of base models, startning training, basic tweaking, and looking at your logs
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### [Multiaspect and crop jitter explainer](https://www.youtube.com/watch?v=0xswM8QYFD0)
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Behind the scenes look at how the trainer handles multiaspect and crop jitter
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## Cloud/Docker
### [Free tier Google Colab notebook](https://colab.research.google.com/github/victorchall/EveryDream2trainer/blob/main/Train_Colab.ipynb)
### * [RunPod / Vast Instructions](/doc/CLOUD_SETUP.md)
#### * [Vast.ai Video Tutorial](https://www.youtube.com/watch?v=PKQesb4om9I)
#### [Runpod Video Tutorial](https://www.youtube.com/watch?v=XAULP-4hsnA)
### [Docker image link](https://github.com/victorchall/EveryDream2trainer/pkgs/container/everydream2trainer)
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## Docs
[Setup and installation ](doc/SETUP.md )
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[Download and setup base models ](doc/BASEMODELS.md )
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[Data Preparation ](doc/DATA.md )
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[Training ](doc/TRAINING.md ) - How to start training
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[Troubleshooting ](doc/TROUBLESHOOTING.md )
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[Basic Tweaking ](doc/TWEAKING.md ) - Important args to understand to get started
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[Advanced Tweaking ](doc/ADVANCED_TWEAKING.md ) and [Advanced Optimizer Tweaking ](/doc/OPTIMIZER.md )
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[Chaining training sessions ](doc/CHAINING.md ) - Modify training parameters by chaining training sessions together end to end
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[Shuffling Tags ](doc/SHUFFLING_TAGS.md )
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[Data Balancing ](doc/BALANCING.md ) - Includes my small treatise on model "preservation" with additional ground truth data
[Logging ](doc/LOGGING.md )
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[Validation ](doc/VALIDATION.md ) - Use a validation split on your data to see when you are overfitting and tune hyperparameters
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[Captioning ](doc/CAPTION.md ) - tools to generate synthetic captioning (recommend [Cog ](doc/CAPTION_COG.md ))
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[Plugins ](doc/PLUGINS.md ) - (beta) write your own plugins to execute arbitrary code during training
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[Contributing ](doc/CONTRIBUTING.md )
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[Citations and references ](doc/CITATIONS.md )