mlx-swift-lm Skill

1. Overview & Triggers

mlx-swift-lm is a Swift package for running Large Language Models (LLMs) and Vision-Language Models (VLMs) on Apple Silicon using MLX. It supports local inference, streaming generation, wired-memory coordination, tool calling, LoRA/DoRA fine-tuning, and embeddings.

When to Use This Skill

• Running LLM/VLM inference on macOS/iOS with Apple Silicon
• Streaming text generation from local models
• Coordinating concurrent inference with wired-memory policies and tickets
• Tool calling / function calling with models
• LoRA adapter training and fine-tuning
• Text embeddings for RAG/semantic search
• Porting model architectures from Python MLX-LM to Swift

Architecture Overview

MLXLMCommon     - Core infra (ModelContainer, ChatSession, Evaluate, KVCache, wired memory helpers)
MLXLLM          - Text-only LLM support (Llama, Qwen, Gemma, Phi, DeepSeek, etc.)
MLXVLM          - Vision-Language Models (Qwen-VL, PaliGemma, Gemma3, etc.)
MLXEmbedders    - Embedding models and pooling utilities

2. Key File Reference