---
language:
  - multilingual
license: cc-by-nc-4.0
tags:
  - language-identification
  - coreml
  - ios
  - audio
  - wav2vec2
  - mms-lid
datasets:
  - mms-lid
---

# MMS-LID 256 (Core ML)

Core ML conversion of **MMS-LID** (Massively Multilingual Speech - Language Identification) for **256 languages**. Float16 model for on-device inference on iOS 17+ and macOS.

- **Base model:** [facebook/mms-lid-256](https://huggingface.co/facebook/mms-lid-256)
- **Format:** Core ML (.mlpackage), float16
- **Languages:** 256 (ISO 639-3)

## Contents

- Core ML model (.mlpackage)
- `labels.json` or `mms_lid_id2label.json` – Index to language code mapping

## Input / Output

- **Input:** 16 kHz mono float32 audio, 10 seconds (160,000 samples)
- **Output:** Logits over 256 language classes; `argmax` gives the predicted language index. Map to ISO 639-3 using the labels file.

## Usage (iOS / macOS)

1. Download this repo (e.g. via Hugging Face Hub or in-app download).
2. Load the `.mlpackage` with Core ML; feed 10 seconds of 16 kHz mono audio.
3. Take `argmax` of the logits output and look up the language code in the labels file.

## Quantized variants (same language count)

| Repo | Description |
|------|-------------|
| **this repo** | Float16 Core ML |
| [mms-lid-256-coreml-4bit](https://huggingface.co/aoiandroid/mms-lid-256-coreml-4bit) | 4-bit palettized (smaller, ANE-friendly) |

## Related repos

| Languages | ONNX | Core ML |
|-----------|------|---------|
| 256 | [mms-lid-256-onnx](https://huggingface.co/aoiandroid/mms-lid-256-onnx) | **this repo** |
| 126 | – | [mms-lid-126-coreml](https://huggingface.co/aoiandroid/mms-lid-126-coreml) |
| 512 | – | [mms-lid-512-coreml](https://huggingface.co/aoiandroid/mms-lid-512-coreml) |

## Citation

```bibtex
@article{pratap2023mms,
  title={Scaling Speech Technology to 1,000+ Languages},
  author={Vineel Pratap and Andros Tjandra and Bowen Shi and Paden Tomasello and Arun Babu and Sayani Kundu and Ali Elkahky and Zhaoheng Ni and Apoorv Vyas and Maryam Fazel-Zarandi and Alexei Baevski and Yossi Adi and Xiaohui Zhang and Wei-Ning Hsu and Alexis Conneau and Michael Auli},
  journal={arXiv},
  year={2023}
}
```

## License

CC-BY-NC-4.0 (inherited from MMS-LID).