| --- |
| 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). |
|
|
