mega-asr-mlx 0.1.0

Mega-ASR: fine-tuned Qwen3-ASR 1.7B for Chinese/English code-switching speech recognition on Apple MLX

Mega-ASR MLX

End-to-end speech recognition on Apple Silicon, powered by MLX.

Mega-ASR is a fine-tuned Qwen3-ASR 1.7B model with merged LoRA weights, optimized for Chinese/English code-switching speech. The model runs entirely on-device via Apple MLX.

Install

pip install mega-asr-mlx

Quick Start

# Download model weights from HuggingFace (~4.4 GB)
huggingface-cli download voiceink/mega-asr-mlx --local-dir ~/.cache/voiceink/mega-asr-mlx

# Transcribe audio
mega-asr --audio speech.wav --language English

Or use as a Python library:

from mega_asr_mlx import MegaASRMLX

model = MegaASRMLX("~/.cache/voiceink/mega-asr-mlx")
text = model.transcribe("speech.wav", language="English")
print(text)

Model

Component	Architecture	Size
Audio Encoder	Conv2D stem + 24-layer Transformer (1024-dim)	606 MB
Decoder	Qwen3 28-layer (2048-dim, GQA 16/8)	3.8 GB
Router	4-layer Transformer audio quality classifier	2.2 MB

• Languages: Chinese, English (auto-detect)
• Input: 16 kHz mono WAV
• Output: Plain text transcription

Requirements

• macOS with Apple Silicon (M1/M2/M3/M4)
• Python 3.10+
• Dependencies: mlx, mlx-lm, numpy, scipy, soundfile, safetensors, transformers

License

MIT