DEVELOPER DOCUMENTATION
Build with FastVLM
Start in the browser, reproduce inference in Python, or move to native Apple hardware. Every guide links back to the primary source you should verify before shipping.
FastVLM tooling is evolving. Commands here are grounded in Apple and Hugging Face documentation checked in August 2026; always verify the linked source and pin working dependency versions for production.
Install FastVLM
Clone Apple’s official repository, create an isolated Python environment and install the project for checkpoint inference.
Open guideFastVLM Python Guide
Run image inference with Apple’s official predict.py entry point and a downloaded FastVLM checkpoint.
Open guideFastVLM with Transformers
Understand the official Transformers integration, multimodal chat-template format and model-loading choices.
Open guideFastVLM WebGPU Guide
Run the 0.5B browser demo with Transformers.js and WebGPU, and diagnose browser compatibility issues.
Open guideFastVLM on Hugging Face
Find the official Apple model collection, choose 0.5B, 1.5B or 7B, and review each model card before downloading.
Open guideRun FastVLM on Mac
Choose between the official MLX demo workflow and exported Apple Silicon model resources.
Open guideFastVLM on iPhone and iOS
Use Apple’s official iOS/macOS demo project as the starting point for an on-device FastVLM application.
Open guideFastVLM with Core ML
Review Apple’s released Core ML resources and choose quantization deliberately for your target hardware.
Open guideFastVLM with MLX
Use the MLX-based app and official Apple Silicon checkpoints for native experiments on Mac and iOS.
Open guide