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

* issue ostris#76, load_checkpoint_and_dispatch() 'force_hooks'

ostris#76

* RunPod cloud config

ostris#90

* change 2x A40 to 1x A40 and price per hour

referring to ostris#90 (comment)

* include missed FLUX.1-schnell setup guide in last commit

* huggingface-cli login required auth

README.md

@@ -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">
+
+<!---
 ### Training in the cloud
 Coming very soon. Getting base out then will have a notebook that makes all that work. 
+-->
 
 ---
 

requirements.txt

@@ -27,4 +27,5 @@ hf_transfer
 lpips
 pytorch_fid
 optimum-quanto
-sentencepiece
+sentencepiece
+huggingface_hub