MODEL: Qwen 2.5

DATASET: QA Benchmark

AGENTS: 4 Active

RAM: 28.7 GB - 98.1 GB

GPU: 26.2 % Usage

Introduction and Background

Introduction and Background

Introduction and Background

This framework enables autonomous research experiments using large language models as intelligent agents. The system supports multiple concurrent agents working together to solve complex research problems.

Key Features

• Multi-agent coordination

• Automated experiment pipeline

• Real-time result analysis

• Extensible agent framework

Example API Request:

def run_experiment(model, dataset): results [l for agent in agents: agent . initialize(model) result = agent. analyze(dataset) results. append( result) return aggregate _ results( results)