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Decentralized AI Network

Project description

NeuroShard AI

Decentralized AI Training Network

PyPI version Python 3.9+ License: MIT

Quick Start

# Install
pip install nexaroa

# Run a node (you'll need a token from neuroshard.com)
neuroshard --token YOUR_TOKEN

What is NeuroShard?

NeuroShard is a decentralized network for training large language models. Contributors share their GPU/CPU power and earn NEURO tokens based on their contribution (Proof of Neural Work).

Key Features

  • Swarm Architecture - Fault-tolerant, multipath routing for resilient training
  • Async Training - DiLoCo-style gradient accumulation for 90%+ bandwidth reduction
  • Earn NEURO - Get rewarded for contributing compute power
  • Cryptographic Proofs - ECDSA-signed Proof of Neural Work
  • Web Dashboard - Monitor your node at http://localhost:8000

Requirements

  • Python 3.9+
  • 4GB+ RAM (8GB+ recommended)
  • GPU optional but recommended for training

GPU Support

For NVIDIA GPU support, install PyTorch with CUDA:

pip install torch --index-url https://download.pytorch.org/whl/cu118

Usage

Basic Node

neuroshard --token YOUR_TOKEN

With Custom Port

neuroshard --token YOUR_TOKEN --port 9000

Connect to Specific Tracker

neuroshard --token YOUR_TOKEN --tracker tracker.neuroshard.com:8080

Web Dashboard

Once running, open your browser to http://localhost:8000 to view:

  • Node status and role
  • Network statistics
  • Training progress
  • NEURO balance
  • Resource usage

Architecture

NeuroShard uses a swarm-based architecture for maximum resilience:

  • Dynamic Routing - If one node fails, work automatically routes to others
  • Activation Buffering - GPUs never starve waiting for network
  • DiLoCo Training - Local gradient accumulation reduces sync frequency by 90%+
  • Speculative Checkpoints - Fast recovery from node failures

Links

License

MIT License - see LICENSE for details.

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