flow-nexus-neural

Train and deploy neural networks in distributed E2B sandboxes using Flow Nexus.

• Train custom or pre-built neural models in distributed environments.
• Use multiple architectures including feedforward, LSTM, GAN, and transformer.
• Scale training across clusters with decentralized autonomy and consensus.
• Deploy and manage models via marketplace templates.

• Support for feedforward, LSTM, GAN, transformer, and autoencoder architectures.
• Distributed training across E2B sandboxes with mesh, ring, or star topologies.
• Customizable training tiers: nano to large with resource scaling.
• Pre-built templates for quick deployment in classification, NLP, vision, etc.
• Support for divergent training with lateral, quantum, or chaotic patterns.
• Model inference with real-time predictions and latency reporting.
• Decentralized autonomous agents (DAAs) with consensus mechanisms.
• Worker and parameter server nodes with configurable autonomy and roles.

1. 1.Add Flow Nexus MCP server and register/login via CLI.
2. 2.Use mcp__flow-nexus__neural_train to configure and train models with architecture and training settings.
3. 3.Deploy models via mcp__flow-nexus__neural_deploy_template from marketplace.
4. 4.Initialize clusters and deploy worker/parameter nodes for distributed training.