NeuroShard
Decentralized LLM Training Network
Website • Documentation • Whitepaper • Discord • Twitter
What is NeuroShard?
NeuroShard is a decentralized network for training large language models. Anyone can contribute GPU/CPU power and earn NEURO tokens through Proof of Neural Work.
Unlike centralized AI companies, NeuroShard distributes both the compute AND the rewards across all participants.
Key Features
| Feature | Description |
|---|---|
| DiLoCo Training | Distributed Low-Communication training - sync every 500 steps, not every step |
| Byzantine Tolerance | Robust gradient aggregation (Krum, Trimmed Mean) handles malicious nodes |
| NEURO Rewards | Earn tokens for contributing compute via Proof of Neural Work |
| Cryptographic Proofs | ECDSA-signed proofs ensure trustless verification |
| Web Dashboard | Real-time monitoring at http://localhost:8000 |
| P2P Network | Decentralized peer discovery and gossip protocol |
Quick Start
Installation
pip install neuroshard
Run a Node
# Get your token from neuroshard.com
neuroshard --token YOUR_TOKEN
That's it! Your node will:
- Connect to the network
- Start training model layers
- Earn NEURO for your contribution
Web Dashboard
Open http://localhost:8000 to see:
- Node status and role
- Training progress (DiLoCo inner/outer steps)
- NEURO balance
- Network statistics
System Requirements
| Component | Minimum | Recommended |
|---|---|---|
| RAM | 4 GB | 8+ GB |
| Python | 3.9+ | 3.10+ |
| GPU | Optional | NVIDIA 8GB+ VRAM |
GPU Support (Optional)
For NVIDIA GPUs with CUDA:
pip install torch --index-url https://download.pytorch.org/whl/cu118
How It Works
DiLoCo Distributed Training
NeuroShard uses DiLoCo (Distributed Low-Communication) for efficient distributed training:
┌─────────────────────────────────────────────────┐
│ INNER LOOP (500 steps - no communication) │
│ • Each node trains independently │
│ • Local AdamW optimization │
└─────────────────────────────────────────────────┘
↓
┌─────────────────────────────────────────────────┐
│ OUTER LOOP (sync with peers) │
│ • Compute pseudo-gradient: Δθ = θ₀ - θ₅₀₀ │
│ • Gossip to peers │
│ • Byzantine-tolerant aggregation │
│ • Nesterov momentum update │
└─────────────────────────────────────────────────┘
↓
(Repeat)
This reduces network communication by 500x compared to synchronous training!
Proof of Neural Work
Nodes earn NEURO by submitting cryptographically signed proofs of their work:
- Training batches processed
- Inference requests served
- Uptime contribution
- Data samples provided
All proofs are verified using ECDSA signatures (secp256k1).
Configuration
CLI Options
neuroshard --token YOUR_TOKEN \
--port 8000 \
--tracker https://tracker.neuroshard.com \
--training \
--diloco-steps 500
| Option | Default | Description |
|---|---|---|
--token |
Required | Your node authentication token |
--port |
8000 | HTTP server port |
--tracker |
Auto | Tracker server URL |
--training |
False | Enable training mode |
--diloco-steps |
500 | Inner steps before sync |
See full CLI reference for all options.
Architecture
┌─────────────────────────────────────────────────────────────┐
│ NeuroShard Node │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────┐ │
│ │ NeuroLLM │ │ DiLoCo │ │ Proof of Neural │ │
│ │ (Model) │ │ Trainer │ │ Work Ledger │ │
│ └─────────────┘ └─────────────┘ └─────────────────────┘ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────┐ │
│ │ P2P/DHT │ │ Gradient │ │ ECDSA Crypto │ │
│ │ Network │ │ Aggregator │ │ (secp256k1) │ │
│ └─────────────┘ └─────────────┘ └─────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
Documentation
- Whitepaper - Technical whitepaper (PDF)
- Getting Started - First steps
- Running a Node - Detailed setup
- Architecture - System design
- Economics - NEURO tokenomics
- API Reference - SDK & endpoints
Links
| Resource | Link |
|---|---|
| Website | neuroshard.com |
| Documentation | docs.neuroshard.com |
| Whitepaper | |
| Discord | discord.gg/4R49xpj7vn |
| @shardneuro | |
| PyPI | pypi.org/project/neuroshard |
Contributing
We welcome contributions! Please see our Contributing Guide for details.
# Clone the repo
git clone https://github.com/Nexaroa/neuroshard.git
cd neuroshard
# Install dev dependencies
pip install -e ".[dev]"
# Run tests
pytest
License
Apache License 2.0 - see LICENSE for details.
Train AI. Earn NEURO. Own the Network.
1 maintainer
Metadata
1 maintainer
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