issue #76, and RunPod cloud training setup #90 (#80)

* 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
This commit is contained in:
martintomov
2024-08-19 00:43:45 +03:00
committed by GitHub
parent c45887192a
commit 5603f9e004
2 changed files with 45 additions and 1 deletions

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@@ -115,8 +115,51 @@ Please do not open a bug report unless it is a bug in the code. You are welcome
and ask for help there. However, please refrain from PMing me directly with general question or support. Ask in the discord
and I will answer when I can.
### Training in RunPod cloud
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.
#### 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
### 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 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)
- 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
<img width="1728" alt="RunPod Training Screenshot" src="https://github.com/user-attachments/assets/53a1b8ef-92fa-4481-81a7-bde45a14a7b5">
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### Training in the cloud
Coming very soon. Getting base out then will have a notebook that makes all that work.
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