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name: llm-config description: Configure SwarmLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptation argument-hint: "[--model MODEL] [--adapter microlora|sona]" allowed-tools: mcp__swarmdo__swarmllm_generate_config mcp__swarmdo__swarmllm_status mcp__swarmdo__swarmllm_microlora_create mcp__swarmdo__swarmllm_microlora_adapt mcp__swarmdo__swarmllm_sona_create mcp__swarmdo__swarmllm_sona_adapt Bash

LLM Configuration

Configure SwarmLLM for local inference and fine-tuning.

When to use

When you need to configure local LLM inference, create MicroLoRA adapters for task-specific fine-tuning, or set up SONA for real-time adaptation.

Steps

1. Check status — call mcp__swarmdo__swarmllm_status to see current model and adapter state
2. Generate config — call mcp__swarmdo__swarmllm_generate_config with model parameters
3. Create MicroLoRA — call mcp__swarmdo__swarmllm_microlora_create for task-specific adapters
4. Adapt MicroLoRA — call mcp__swarmdo__swarmllm_microlora_adapt with training data
5. Create SONA — call mcp__swarmdo__swarmllm_sona_create for real-time neural adaptation
6. Adapt SONA — call mcp__swarmdo__swarmllm_sona_adapt with feedback signals

MicroLoRA vs SONA

| Feature | MicroLoRA | SONA | |---------|-----------|------| | Speed | Minutes to train | <0.05ms adaptation | | Scope | Task-specific fine-tuning | Real-time micro-adjustments | | Persistence | Saved as adapter weights | Session-scoped | | Use case | Specialized domain tasks | Continuous feedback loops |