

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

Example tutorial for learn how to install and use RunPod is below

(starts at 22:03) : https://youtu.be/KW-MHmoNcqo?si=QN8X8Sjn13ZYu-EU&t=1323

RunPod permanent network storage tutorial : https://youtu.be/8Qf4x3-DFf4

Select below template mandatory

Runpod Pytorch 2.1
runpod/pytorch:2.1.0-py3.10-cuda11.8.0-devel-ubuntu22.04

Ignore RunPod warning and select above template even for RTX 5090 or RTX 6000 PRO - it will work

Upload everything into workspace folder

To install run below command

Edit the pod configuration:
Set the volume disk size to 50 GB or your preferred size according to number of models you want to download or such.

Add HTTP port 7861 to the exposed ports list to enable proxy connection.
By default, it will start with the --share option for Gradio sharing.

Upload all files to the workspace folder.

To install, run the following commands:


export HF_HOME="/workspace"
chmod +x Runpod_Install.sh
./Runpod_Install.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
source venv/bin/activate
python 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 turn off your pod after installation and restart run below command 1 time

