Cloud Agents for Distributed Model Training
A lightweight and horizontally scalable distributed computing system for training large language models, specifically designed for OpenPeerLLM.
Features
- Distributed tensor operations for model training
- CouchDB-based coordination layer
- Automatic agent discovery and load balancing
- Horizontal scaling capabilities
- Fault tolerance and recovery
- Integration with OpenPeerAI's OpenPeerLLM
Installation
pip install -r requirements.txt
Configuration
- Set up CouchDB instance
- Copy
.env.example
to.env
and configure your settings - Start the coordinator node
- Launch agent nodes
Quick Start
# Start coordinator
python -m cloud_agents.coordinator
# Start agent (on each machine)
python -m cloud_agents.agent
Architecture
coordinator
: Manages job distribution and agent coordinationagent
: Handles tensor operations and model trainingcouchdb_client
: Interface for CouchDB communicationtensor_ops
: Distributed tensor operationsutils
: Helper functions and utilities
License
MIT
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Base model
OpenPeerAI/OpenPeerLLM