diff --git a/README.md b/README.md index d987f585..e3118fdf 100644 --- a/README.md +++ b/README.md @@ -287,45 +287,12 @@ You will instantiate a UI that will let you upload your images, caption them, tr ## Training in RunPod -Example RunPod template: **runpod/pytorch:2.2.0-py3.10-cuda12.1.1-devel-ubuntu22.04** -> You need a minimum of 24GB VRAM, pick a GPU by your preference. +If you would like to use Runpod, but have not signed up yet, please consider using [my Runpod affiliate link](https://runpod.io?ref=h0y9jyr2) to help support this project. -#### Example config ($0.5/hr): -- 1x A40 (48 GB VRAM) -- 19 vCPU 100 GB RAM -#### Custom overrides (you need some storage to clone FLUX.1, store datasets, store trained models and samples): -- ~120 GB Disk -- ~120 GB Pod Volume -- Start Jupyter Notebook +I maintain an official Runpod Pod template here which can be accessed [here](https://console.runpod.io/deploy?template=0fqzfjy6f3&ref=h0y9jyr2). -### 1. Setup -``` -git clone https://github.com/ostris/ai-toolkit.git -cd ai-toolkit -git submodule update --init --recursive -python -m venv venv -source venv/bin/activate -pip install torch -pip install -r requirements.txt -pip install --upgrade accelerate transformers diffusers huggingface_hub #Optional, run it if you run into issues -``` -### 2. Upload your dataset -- Create a new folder in the root, name it `dataset` or whatever you like. -- Drag and drop your .jpg, .jpeg, or .png images and .txt files inside the newly created dataset folder. - -### 3. Login into Hugging Face with an Access Token -- Get a READ token from [here](https://huggingface.co/settings/tokens) and request access to Flux.1-dev model from [here](https://huggingface.co/black-forest-labs/FLUX.1-dev). -- Run ```huggingface-cli login``` and paste your token. - -### 4. Training -- Copy an example config file located at ```config/examples``` to the config folder and rename it to ```whatever_you_want.yml```. -- Edit the config following the comments in the file. -- Change ```folder_path: "/path/to/images/folder"``` to your dataset path like ```folder_path: "/workspace/ai-toolkit/your-dataset"```. -- Run the file: ```python run.py config/whatever_you_want.yml```. - -### Screenshot from RunPod -RunPod Training Screenshot +I have also created a short video showing how to get started using AI Toolkit with Runpod [here](https://youtu.be/HBNeS-F6Zz8). ## Training in Modal