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MMS ASR

MLX implementation of Meta's Massively Multilingual Speech (MMS) ASR model, supporting 1000+ languages through language-specific adapter layers on top of a shared wav2vec2 backbone.

Available Models

Model Parameters Languages Description
facebook/mms-1b-fl102 1B 102 Finetuned on FLEURS
facebook/mms-1b-all 1B 1162 All supported languages

Python Usage

from mlx_audio.stt import load

model = load("facebook/mms-1b-fl102")

result = model.generate("audio.wav")
print(result.text)

Architecture

  • Wav2Vec2 encoder with convolutional feature extractor
  • Per-layer attention adapter modules for language adaptation
  • CTC head with language-specific vocabulary
  • Adapter weights loaded automatically from adapter.{lang}.safetensors
  • 16kHz audio input with zero-mean unit-variance normalization