---
title: mms-cclms
canonical_url: "https://www.modelscope.cn/models/facebook/mms-cclms"
md_url: "https://www.modelscope.cn/models/facebook/mms-cclms.md"
repository: facebook/mms-cclms
last_updated: 2025-05-20
license: cc-by-nc-4.0
library_name:
  - pytorch
frameworks:
  - pytorch
downloads: 290
stars: 0
tags:
  - mms
---

# mms-cclms

> mms-cclms - facebook 在 ModelScope 开源的模型。Massively Multilingual Speech (MMS) - Common Crawl Language Models

facebook/mms-cclms 是 ModelScope 魔搭社区上的机器学习模型，采用 cc-by-nc-4.0 许可。

- **Repository**: facebook/mms-cclms
- **License**: cc-by-nc-4.0
- **Tags**: mms
- **Downloads**: 290
- **Stars**: 0
- **Last updated**: 2025-05-20

Source: https://www.modelscope.cn/models/facebook/mms-cclms

---

# Massively Multilingual Speech (MMS) - Common Crawl Language Models

This repository consists of the n-gram language models trained on Common Crawl data ([Conneau et al. 2020b](https://aclanthology.org/2020.acl-main.747/), [NLLB_Team et al. 2022](https://arxiv.org/abs/2207.04672)) using [KenLM library](https://github.com/kpu/kenlm). 


For the following languages, the LMs are not present in the repository (due to 50GB limit on HuggingFace) and can be downloaded using the link provided here. 

Mandarin Chinese (Simplified) - [Download LM](https://dl.fbaipublicfiles.com/mms/lms/cmn-script_simplified/char_20gram.bin)

Japanese - [Download LM](https://dl.fbaipublicfiles.com/mms/lms/jpn/char_20gram.bin)

Thai - [Download LM](https://dl.fbaipublicfiles.com/mms/lms/tha/char_20gram.bin)

Cantonese(Traditional) - [Download LM](https://dl.fbaipublicfiles.com/mms/lms/yue-script_traditional/char_20gram.bin)

## Table Of Content

- [Example](#example)
- [Supported Languages](#supported-languages)
- [Model details](#model-details)
- [Additional links](#additional-links)

## Example

Checkout the code here - https://huggingface.co/spaces/mms-meta/MMS/blob/main/asr.py which uses LMs for decoding the output from ASR models. 


## Supported Languages

We support language models in 102 languages. Unclick the following to toogle all supported languages of this checkpoint in [ISO 639-3 code](https://en.wikipedia.org/wiki/ISO_639-3).
You can find more details about the languages and their ISO 639-3 codes in the [MMS Language Coverage Overview](https://dl.fbaipublicfiles.com/mms/misc/language_coverage_mms.html).
<details>
  <summary>Click to toggle</summary>
  
 - afr
 - amh
 - ara
 - asm
 - ast
 - azj
 - bel
 - ben
 - bos
 - bul
 - cat
 - ceb
 - ces
 - ckb
 - cmn
 - cym
 - dan
 - deu
 - ell
 - eng
 - est
 - fas
 - fin
 - fra
 - ful
 - gle
 - glg
 - guj
 - hau
 - heb
 - hin
 - hrv
 - hun
 - hye
 - ibo
 - ind
 - isl
 - ita
 - jav
 - jpn
 - kam
 - kan
 - kat
 - kaz
 - kea
 - khm
 - kir
 - kor
 - lao
 - lav
 - lin
 - lit
 - ltz
 - lug
 - luo
 - mal
 - mar
 - mkd
 - mlt
 - mon
 - mri
 - mya
 - nld
 - nob
 - npi
 - nso
 - nya
 - oci
 - orm
 - ory
 - pan
 - pol
 - por
 - pus
 - ron
 - rus
 - slk
 - slv
 - sna
 - snd
 - som
 - spa
 - srp
 - swe
 - swh
 - tam
 - tel
 - tgk
 - tgl
 - tha
 - tur
 - ukr
 - umb
 - urd
 - uzb
 - vie
 - wol
 - xho
 - yor
 - yue
 - zlm
 - zul
</details>

## Model details

- **Developed by:** Vineel Pratap et al.
- **Model type:** Multi-Lingual Automatic Speech Recognition model
- **Language(s):** 126 languages, see [supported languages](#supported-languages)
- **License:** CC-BY-NC 4.0 license
- **Num parameters**: 1 billion
- **Audio sampling rate**: 16,000 kHz
- **Cite as:**

      @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}
      }

## Additional Links

- [Blog post](https://ai.facebook.com/blog/multilingual-model-speech-recognition/)
- [Transformers documentation](https://huggingface.co/docs/transformers/main/en/model_doc/mms).
- [Paper](https://arxiv.org/abs/2305.13516)
- [GitHub Repository](https://github.com/facebookresearch/fairseq/tree/main/examples/mms#asr)
- [Other **MMS** checkpoints](https://huggingface.co/models?other=mms)
- MMS base checkpoints:
  - [facebook/mms-1b](https://huggingface.co/facebook/mms-1b)
  - [facebook/mms-300m](https://huggingface.co/facebook/mms-300m)
- [Official Space](https://huggingface.co/spaces/facebook/MMS)