# How to train a new person in Stable Diffusion using Dreambooth Assumes you have a runpod (https://www.runpod.io/) account with credits * Choose Secure Cloud and 1x RTX A5000 machine (something with > 24GB RAM) * Select template "Run Pod PyTorch" * Container Disk and Volume Disk = 40GB * "start jupiter notebook" ticked * Click Continue * Click on My Pods * Click on `connect` * Click on `connect to jupiter lab` * click on Python3 (notebook) * Paste this `!git clone https://github.com/JoePenna/Dreambooth-Stable-Diffusion.git` into the console area and press the play icon * A new folder `Dreambooth-Stable-Diffusion` should appear in the right window. You may need to press the refresh symbol. Double click this folder to enter. * Now double click on the file `dreambooth_runpod_joepenna.ipynb`. This should open a new tab (you can delete the other one if you wish) * In `Build Environment` you can now choose the second box and press play to install a bunch of python dependencies as we have already done the first one. You know when a cell has completed as the `*` turns into a number. * Before we run the next cell we need to create a hugging face token. Visit https://huggingface.co and create an account (its free) if you don't have one already. * Logged into your new account go to https://huggingface.co/settings/tokens * create a new token with `write` access * You will also need to accept the t&c's for the Stable Diffusion version you are about to download so visit https://huggingface.co/CompVis/stable-diffusion-v-1-4-origin * Back in runpod you can now run the cell and enter the new token into the box and press play * You should now be able to run the next cell which downloads the 1.4 stable diffusion model * Next we need some Regularization Images. I used the pre-generated ones so used that cell. * Now we upload our training images. I created a folder called `training_images` and dragged my images into that folder rather than provide urls. I pre-sized them using a local running version SD and using the train/precreateimages tab. They need to be `.pngs` and `512x512`. * You are now ready to train. You need to fill in `project` as a unique name for your project, the important bits are `class_word` and `token`. For the purpose of training a mayself I used `person` and `duncan_robertson`. * The final part is `max_training_steps` * For the max_training_steps I used the amount of training images I had uploaded * 100 * You can now run this cell. It takes about 1 hour * Once complete you can then run the next cell which moves the last checkpoint file into the trained_models folder. * You can now download this folder as this is the newly trained model you can use in your local Stable Diffusion setup.