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* issue #76, load_checkpoint_and_dispatch() 'force_hooks' https://github.com/ostris/ai-toolkit/issues/76 * RunPod cloud config https://github.com/ostris/ai-toolkit/issues/90 * change 2x A40 to 1x A40 and price per hour referring to https://github.com/ostris/ai-toolkit/issues/90#issuecomment-2294894929 * include missed FLUX.1-schnell setup guide in last commit * huggingface-cli login required auth
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README.md
43
README.md
@@ -115,8 +115,51 @@ Please do not open a bug report unless it is a bug in the code. You are welcome
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and ask for help there. However, please refrain from PMing me directly with general question or support. Ask in the discord
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and I will answer when I can.
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### Training in RunPod cloud
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Example RunPod template: **runpod/pytorch:2.2.0-py3.10-cuda12.1.1-devel-ubuntu22.04**
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> You need a minimum of 24GB VRAM, pick a GPU by your preference.
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#### Example config ($0.5/hr):
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- 1x A40 (48 GB VRAM)
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- 19 vCPU 100 GB RAM
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#### Custom overrides (you need some storage to clone FLUX.1, store datasets, store trained models and samples):
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- ~120 GB Disk
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- ~120 GB Pod Volume
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- Start Jupyter Notebook
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### 1. Setup
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```
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git clone https://github.com/ostris/ai-toolkit.git
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cd ai-toolkit
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git submodule update --init --recursive
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python -m venv venv
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source venv/bin/activate
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pip install torch
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pip install -r requirements.txt
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pip install --upgrade accelerate transformers diffusers huggingface_hub #Optional, run it if you run into issues
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```
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### 2. Upload your dataset
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- Create a new folder in the root, name it `dataset` or whatever you like
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- Drag and drop your .jpg and .txt files inside the newly created dataset folder
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### 3. Login into Hugging Face with an Access Token
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- Get a READ token from [here](https://huggingface.co/settings/tokens)
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- Run ```huggingface-cli login``` and paste your token
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### 4. Training
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- Copy an example config file located at ```config/examples``` to the config folder and rename it to ```whatever_you_want.yml```
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- Edit the config following the comments in the file
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- Change ```folder_path: "/path/to/images/folder"``` to your dataset path like ```folder_path: "/workspace/ai-toolkit/your-dataset"```
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- Run the file: ```python run.py config/whatever_you_want.yml```
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### Screenshot from RunPod
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<img width="1728" alt="RunPod Training Screenshot" src="https://github.com/user-attachments/assets/53a1b8ef-92fa-4481-81a7-bde45a14a7b5">
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<!---
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### Training in the cloud
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Coming very soon. Getting base out then will have a notebook that makes all that work.
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-->
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---
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