README.md

metadata

license: mit
datasets:
  - fka/awesome-chatgpt-prompts
language:
  - en
library_name: cloud-agents
metrics:
  - accuracy
  - code_eval
base_model:
  - OpenPeerAI/OpenPeerLLM
tags:
  - agent
  - cloud
  - computing
  - distributed
  - distributed-learning
  - decentralized
  - grid
  - grid-computing
  - machine-learning
  - ml

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

1. Set up CouchDB instance
2. Copy .env.example to .env and configure your settings
3. Start the coordinator node
4. 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 coordination
• agent: Handles tensor operations and model training
• couchdb_client: Interface for CouchDB communication
• tensor_ops: Distributed tensor operations
• utils: Helper functions and utilities

License

MIT