This project provides tools to fine-tune Whisper models using LoRA for efficient adaptation. It supports training on data with or without timestamps, and even on non-speech audio. The repository includes utilities for accelerating inference using CTranslate2 and GGML backends, enabling deployment on web interfaces, Windows desktop applications, and Android devices. Multiple Whisper model sizes from tiny to large-v3 are supported.