facebook/mms-1b-all

automatic-speech-recognition model by facebook

From the publisher

Model card & documentation

Source preview

Read the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.

This checkpoint is a model fine-tuned for multi-lingual ASR and part of Facebook's Massive Multilingual Speech project. This checkpoint is based on the Wav2Vec2 architecture and makes use of adapter models to transcribe 1000+ languages. The checkpoint consists of 1 billion parameters and has been fine-tuned from facebook/mms-1b on 1162 languages. This MMS checkpoint can be used with Transformers to transcribe audio of 1107 different languages. Let's look at a simple example. First, we install transformers and some other libraries Note: In order to use MMS you need to have at least transformers >= 4.30 installed. If the 4.30 version is not yet available on PyPI make sure to install transformers from source: Next, we load a couple of audio samples via datasets. Make sure that the audio data is sampled to 16000 kHz. Next, we load the model and processor Now we process the audio data, pass the processed…

facebook/mms-1b-all on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-09-26T06:49:46.790Z

Inside the original model card — Document outline

Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.

Links from the model card

References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.

Documentation belongs to its respective authors. Reported project/model license: cc-by-nc-4.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

facebook/mms-1b-all is a automatic-speech-recognition model repository published by facebook on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task: automatic-speech-recognition
Library: transformers
Recent downloads (30 days): 299,174
Cumulative likes: 206
Hugging Face trending score: 1
Reported safetensors parameters: 964,845,850
Architecture: Wav2Vec2ForCTC
License: cc-by-nc-4.0
Access: Not gated by Hugging Face
Created: 2023-05-27T11:43:21.000Z
Last modified: 2023-06-15T10:45:44.000Z

Compatibility and lineage

Reported languages: ab, af, ak, am, ar, as, av, ay, az, ba, bm, be, bn, bi, bo, sh, br, bg, ca, cs, ce, cv, ku, cy, da, de, dv, dz, el, en, eo, et, eu, ee, fo, fa, fj, fi, fr, fy

Base-model lineage was not included.

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

Use and evaluate

Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.

No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.

Model card and usage instructions

Model files and configuration

Community discussion