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Hypertensor Subnet LLM Template

An incentivized intelligence template for running P2P large language models within the Hypertensor network with a POI (Proof of Inference) consensus mechanism, and POS (Proof of Stake) consensus mechanism.

Read the whitepaper

Read the full documentation to start an incentivized subnet validator node.

Getting Started

  • Clone repository
  • Create an .env file in the root directory by copying .env.example and fill in the variables.
  • Add virtual environment (optional):
    • python -m venv .venv
    • source .venv/bin/activate
  • Install: python -m pip install .
  • Generate Ed25519 private key (Required for validator node): python -m subnet.cli.crypto.keygen

Basic Usage

Start your own subnet:

python -m subnet.cli.run_server_validator bigscience/bloom-560m --host_maddrs /ip4/0.0.0.0/tcp/{PORT} ip4/0.0.0.0/udp/{PORT}/quic --announce_maddrs ip4/{IP}/tcp/{PORT}/ip4/{IP}/udp/{PORT}/quic --identity_path {PRIVATE_KEY_PATH} --new_swarm

Start your own subnet validator node:

python -m subnet.cli.run_server_validator bigscience/bloom-560m --public_ip {IP} --port {PORT} --initial_peers {INITIAL_PEERS} --identity_path {PRIVATE_KEY_PATH}

Instead of using --initial_peers, the constants.py file can be updated to include them. Read the full documentation or the cli directory for all available arguments.