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Dreambooth GUI Installation - Train AI on Windows

2023-12-01 19:46 Learn AI

Overview

There are many ways to fine-tune stable diffusion to your specific styles or images. This time we run it locally on a Windows machine using smy20011 / dreambooth-gui (link).
In our previous posts, we wrote how to do the same using third-party services like astria.ai (post link) or how to run it on a rented cloud GPU (post link).

Installation

Installing Docker

The first step is to install one of the two prerequisites, called Docker.
  • Go to docker.com and click “Download Docker Desktop”.
  • Once downloaded, run it, click ok, and wait.
  • Once finished, click close, and the first step is done.

Installing WSL (Windows Subsystem for Linux)

The second prerequisite is WSL2.
  • Run CMD as admin by clicking the Windows icon, typing CMD, right-clicking on the icon, and selecting “Run as Administrator. A black window will pop up.
  • In the window, type “wsl --install”, hit enter, and wait.

Launching Docker

  • Launch the Docker we just installed and click accept.
At this point, it’s common to encounter an error. Here is a fix if you see it:

  • Launch the downloaded file, click next, and finish.
  • Now you need to restart the Docker. If all goes well, you’ll see:
  • If Docker is still giving errors, restart the computer, which usually solves it.

Install Dreambooth GUI

  • Visit GUI Github, and download the x64 installer.
  • If Windows gives you a warning, click Run anyway.
  • Click next, select installation path, click install and wait.

Running GUI and Training

Note: this is just a quick overview with no details about image formats, settings, etc. The goal is to get this GUI running and training for now.
  • Once you run the installed GUI, it will have a simple UI with a few tabs.
  • From the first tab, “Pick Image” select a folder where you have a few training images. (tubes are not there by default, I selected them)
  • In the next tab, “Config Trainer” make sure to enter your Class Prompt (something generic like “person”) and edit training steps and learning rates.
  • Under training arguments, make sure to at least have these lines (or more if you know about Dreambooth training details)
--mixed_precision=fp16
--train_batch_size=1
--gradient_accumulation_steps=1
--use_8bit_adam
--resolution=512
--gradient_checkpointing
--train_text_encoder

  • On the last tab (Train), set the output destination folder; just keep in mind these files get large.
  • If you don’t have a huggingface token:
  • Go to https://huggingface.co/ and create an account.
  • Log in there, click your profile icon on the top right corner, and click settings.
  • Under the settings, click “Access Tokens”, click “New Token,” and copy generated token to the clipboard.
  • Now paste it to GUI under “Hugging Face Token”.
  • Done - press Start. The first run will take longer as it installs all the required packages.
  • It will take some time and generate a cpkt file in the folder that you selected for results.
  • You can copy and paste the cpkt file to your Stable Diffusion models. If you want to run it with WebUI, check out our previous post. Link