Running on Windows Using WSL

You can run the Decentralized LLM Standard subnet on Windows using WSL or Docker. In this guide, we will show you how to set up a subnet validator node on WSL (Windows Subsystem for Linux).

Tutorial

1. This tutorial works on Windows 10-11 and NVIDIA GPUs with driver version >= 495 (this requirement is usually met for fresh installations).

   If you have an AMD GPU, please proceed until you have errors, then upgrade to a patched version of the Subnet mentioned in the AMD GPU tutorial.

2. Launch Windows PowerShell as an Administrator, and install WSL 2:

   wsl.exe --install

   If you previously had WSL 1, please upgrade as explained here.

3. Update WSL, if needed:

   wsl.exe --update

4. Open WSL, and check that GPUs are available:

   nvidia-smi

5. In WSL, install basic Python stuff:

   sudo apt update
   sudo apt install python3-pip python-is-python3

6. Then, clone the Subnet repository:

   git clone https://github.com/hypertensor-blockchain/subnet-llm-template.git

7. In the directory, check torch was installed by returning True:

   python3 -c "import torch; print(torch.cuda.is_available())"

8. See Getting Started.

Got an error? Check out the "Troubleshooting" page. Most errors are covered there and are easy to fix, including:

• hivemind.dht.protocol.ValidationError: local time must be within 3 seconds of others

• Killed

• torch.cuda.OutOfMemoryError: CUDA out of memory

• If your error is not covered there, let us know in Discord and we will help!

Want to share multiple GPUs? In this case, you'd need to run a separate Subnet validator server for each GPU. Open a separate WSL console for each GPU, then run this in the first console:

CUDA_VISIBLE_DEVICES=0 python -m subnet.cli.run_server Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2

Do the same for each console, replacing CUDA_VISIBLE_DEVICES=0 with CUDA_VISIBLE_DEVICES=1, CUDA_VISIBLE_DEVICES=2, etc.

1. Once all blocks are loaded, check that your server is available on https://dashboard.hypertensor.org If your server is listed as available through a "Relay", please read the section below.

Making the server directly available

If you have a NAT or a firewall, the Decentralized LLM Standard subnet will use relays for NAT/firewall traversal by default, which negatively impacts performance. If your computer has a public IP address, we strongly recommend setting up port forwarding to make the server available directly. We explain how to do it below.

1. Create the .wslconfig file in your user's home directory with the following contents:

   [wsl2]
   localhostforwarding=true

2. In WSL, find out the IP address of your WSL container (172.X.X.X):

   sudo apt install net-tools
   ifconfig

3. Allow traffic to be routed into the WSL container (replace 172.X.X.X with the IP address from step 1):

   netsh interface portproxy add v4tov4 listenport=31330 listenaddress=0.0.0.0 connectport=31330 connectaddress=172.X.X.X

4. Set up your firewall (e.g., Windows Defender) to allow traffic from the outside world to the port 31330/tcp.

5. If you have a router, set it up to allow connections from the outside world (port 31330/tcp) to your computer (port 31330/tcp).

Relay servers in the Decentralized LLM Standard subnet receive lesser rewards by default.