87 lines
3.3 KiB
Markdown
87 lines
3.3 KiB
Markdown
# 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/AkUbqnDgYu)
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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.
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[![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
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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
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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
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### [Basic setup and getting started](https://www.youtube.com/watch?v=OgpJK8SUW3c)
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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
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### [Free tier Google Colab notebook](https://colab.research.google.com/github/victorchall/EveryDream2trainer/blob/main/Train_Colab.ipynb)
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### * [RunPod / Vast Instructions](/doc/CLOUD_SETUP.md)
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#### * [Vast.ai Video Tutorial](https://www.youtube.com/watch?v=PKQesb4om9I)
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#### [Runpod Video Tutorial](https://www.youtube.com/watch?v=XAULP-4hsnA)
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### [Docker image link](https://github.com/victorchall/EveryDream2trainer/pkgs/container/everydream2trainer)
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## Docs
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[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
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[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_COG.md) - Llava, Cog, etc. to generate synthetic captioning (or [Old scripts for git/blip](doc/CAPTION.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)
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