To successfully set up and run a Gensyn Testnet node on an Ubuntu system, follow this comprehensive step-by-step guide:

Prerequisites:

• Operating System: Ubuntu 22.04
• Hardware Requirements:
  • CPU: Minimum 16GB RAM; more RAM (e.g., 32GB+) is recommended for larger models or datasets.
  • GPU (Optional): For enhanced performance, CUDA-supported devices are recommended, such as:
    • NVIDIA RTX 3090
    • NVIDIA RTX 4093
    • NVIDIA A100
    • NVIDIA H100
    • Note: The node can also run in CPU-only mode without a GPU.

Step 1: Update System Packages

Begin by updating your system's package list and upgrading existing packages:

sudo apt-get update && sudo apt-get upgrade -y

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Step 2: Install Essential Dependencies

Install the necessary utilities and tools required for the setup:

sudo apt-get install -y python3 python3-venv python3-pip curl wget screen git lsof

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Step 3: Install Node.js and npm

Install Node.js (version 22.x) and npm:

curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash -
sudo apt-get install -y nodejs

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Verify the installation:

node -v

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Step 4: Install Yarn

Set up Yarn, a package manager:

curl -o- -L https://yarnpkg.com/install.sh | bash
export PATH="$HOME/.yarn/bin:$HOME/.config/yarn/global/node_modules/.bin:$PATH"
source ~/.bashrc

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Confirm Yarn is installed:

yarn -v

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Step 5: Install Docker and Docker Compose

Docker is essential for containerized applications:

# Add Docker's official GPG key:
sudo apt-get update
sudo apt-get install ca-certificates curl
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc

# Add the repository to Apt sources:
echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
  $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
sudo apt-get update

# Install Docker packages:
sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

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Verify Docker installation:

docker --version

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Step 6: Obtain a Hugging Face Access Token

1- Create account in HuggingFace

2- Create an Access Token with Write permissions here and save it

1. Create an account on Hugging Face.
2. Navigate to your account settings and generate an Access Token with 'Write' permissions.
3. Save this token securely; it will be required later.

Step 7: Clone the RL Swarm Repository

Download the RL Swarm project from GitHub:

git clone https://github.com/gensyn-ai/rl-swarm.git
cd rl-swarm

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Step 8: Run the RL Swarm Node

To ensure the node continues running even after closing the terminal, use screen:

1. Start a new screen session:

   screen -S gensyn

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2. Set up a Python virtual environment and activate it:

   python3 -m venv .venv
   source .venv/bin/activate

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3. Execute the setup script:

   ./run_rl_swarm.sh

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4. During the setup, you'll be prompted with:

   • "Would you like to connect to the Testnet? [Y/n]": Type Y and press Enter.
   • "Would you like to push models you train in the RL swarm to the Hugging Face Hub? [y/N]": Type y and press Enter.
   • "Please enter your Hugging Face access token:": Input the token you obtained earlier.

5. Once the setup completes, you can detach from the screen session by pressing Ctrl + A, then D. This allows the node to run in the background.

Step 9: Monitor Node Activity

To reattach to the screen session and monitor the node:

screen -r gensyn

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To detach again, press Ctrl + A, then D.

Additional Resources:

• Official Gensyn Testnet Page: Provides an overview and additional details about the testnet. citeturn0search5
• Community Support: For assistance and to engage with other participants, consider joining the Gensyn Discord community.

By following these