Gensyn Testnet Node Guide
Requirement
Details
CPU Architecture
arm64 or amd64
Recommended RAM
25 GB
CUDA Devices (Recommended)
RTX 3090, RTX 4090, A100, H100
Python Version
Python >= 3.10 (For Mac, you may need to upgrade)
Visit : Quick Pod Website
Sign Up using email address
Go to your email and verify your Quick Pod account
Click on Add button in the corner to deposit fund
You can deposit using crypto currency (from metamask) or using Credit card
Now go to template section and then select Ubuntu 22.04 jammy in the below
Now click on Select GPU and search RTX 4090 and choose it
Now choose a GPU and click on Create POD button
Your GPU server will be deployed soon
Now click on Connect option and then choose Connect to web terminal
Install sudo
apt update && apt install -y sudo
Install other dependencies
sudo apt update && sudo apt install -y python3 python3-venv python3-pip curl wget screen git lsof && curl -sS https://dl.yarnpkg.com/debian/pubkey.gpg | sudo apt-key add - && echo " deb https://dl.yarnpkg.com/debian/ stable main" | sudo tee /etc/apt/sources.list.d/yarn.list && sudo apt update && sudo apt install -y yarn
Install Node.js and npm if not installed already
curl -sSL https://raw.githubusercontent.com/zunxbt/installation/main/node.sh | bash
Clone this repository
cd $HOME && [ -d rl-swarm ] && rm -rf rl-swarm; git clone https://github.com/zunxbt/rl-swarm.git && cd rl-swarm
Create a screen session
Run the swarm
python3 -m venv .venv && . .venv/bin/activate && ./run_rl_swarm.sh
It will ask some questions, you should send response properly
Would you like to connect to the Testnet? [Y/n] : Write Y
Would you like to push models you train in the RL swarm to the Hugging Face Hub? [y/N] : Write N
When you will see interface like this, you can detach from this screen session
Detach from screen session
Use Ctrl + A and then press D to detach from this screen session.