
Fast Upload Download Data HuggingFace Tutorial : https://youtu.be/X5WVZ0NMaTg

SIMPLEPOD CHEAPER AND FASTER THAN RUNPOD

Now we fully support SimplePod as well please use this link to register : https://simplepod.ai/ref?user=secourses

SimplePod is faster and cheaper than RunPod and works exactly same

Please use this template on SimplePod : https://dash.simplepod.ai/account/explore/100/ref-secourses/

For permanent storage, generate it from Storage tab with any name and size you want and when selecting template with above link, click Edit and Use, select Persistence Volume and change mount point to /workspace

Up-to-date (22 June 2026) SimplePod tutorial (including how to use permanent storage) starting from 1:03:25 : https://youtu.be/9C_6qNKjgpA?si=ge1XvDomYQ7ssvMu&t=3805

RUNPOD

Please register for RunPod at: https://get.runpod.io/955rkuppqv4h

Up-to-date (22 June 2026) RunPod tutorial (including how to use permanent storage) starting from 31:01 : https://youtu.be/9C_6qNKjgpA?si=vEXM_L4V1L768f9f&t=1861

Select this template mandatory (based on official Runpod Pytorch template) : https://get.runpod.io/SECourses_CU13

Recommended GPU is RTX PRO 5090, but you can use any GPU. The more VRAM it is better

You can edit template and change Volume Disk size. it is by default 200 GB and should be sufficient without any changes

You can also use your permanent storage system - from filters select CUDA 12.8, 12.9, 13 and so on to get newer NVIDIA driver - only NVIDIA driver matter it must be 570+ for CUDA 13

Upload zip file into workspace and extract there or extract in your system and upload all files into workspace

Start a new terminal

To install run below command


cd /workspace
export HF_HOME="/workspace"
export UV_CONCURRENT_INSTALLS=4
chmod +x Runpod_Install_PaintsUndo.sh
./Runpod_Install_PaintsUndo.sh


To use after installation:

Open a new terminal and run the following code each time you start:

This will prompt you to choose which model to load. Run in a new terminal:


cd /workspace
export HF_HOME="/workspace"
export PYTHONWARNINGS="ignore"
export HF_HUB_ENABLE_HF_TRANSFER=1
export CUDA_VISIBLE_DEVICES=0
cd /workspace/Paints-UNDO
git reset --hard
git pull
source venv/bin/activate
python gradio_app.py --share


You will receive a Gradio live link, and you'll be able to connect via the proxy on port 7861.

Pay attention to the Gradio share link among the printed messages.

Remove the --share option if you don't want the Gradio live link

If you rent multiple GPU machine, you can start different instances on each GPU by changing export CUDA_VISIBLE_DEVICES=1 2 3 4 etc

If you stop pod and start again make sure to run installer again 1 more time 
