MLX-VLM provides a Python package for running and fine-tuning Vision Language Models (VLMs) on Apple Silicon Macs using the MLX framework. It targets ML engineers and researchers who want to leverage VLMs locally on their Macs, offering efficient inference and fine-tuning capabilities.

How It Works

The package utilizes the MLX framework, Apple's array computation library, to enable efficient VLM operations on Apple Silicon hardware. It supports loading models from Hugging Face, processing images and text inputs, and generating outputs. The architecture is designed for ease of use, offering both a command-line interface (CLI) and a Gradio-based chat UI for interactive use.

Quick Start & Requirements

• Primary install / run command: pip install mlx-vlm
• Prerequisites: Apple Silicon Mac.
• Links: CLI Usage, Chat UI, Python Script Usage, Server Usage

Highlighted Details

• Supports multi-image analysis and video understanding with select models.
• Enables fine-tuning using LoRA and QLoRA.
• Includes a FastAPI server for dynamic model loading and inference.
• Offers a Gradio-based chat UI for interactive VLM use.

Maintenance & Community

The project is part of the ml-explore organization, indicating active development and community involvement.

Licensing & Compatibility

The README does not explicitly state a license.

Limitations & Caveats

The project is specifically designed for Apple Silicon Macs, limiting its use on other hardware architectures. Support for specific VLM features (like multi-image or video) is model-dependent.