Project AURIONAI Use-Cases Research & Innovation
speech recognition

w2v-bert-2.0

W2v-BERT 2.0 is the self-supervised speech encoder at the core of Meta Seamless models; it needs fine-tuning for ASR or audio classification.

MetaMetaUSA
Meta
Levelmodel
Classspeech recognition
Parameters600M
Contextnot in the notes
Released19 Dec 2023
Opennessopen weights permissive
Runs onnot in the notes
Statusnot in the notes

R&D Topics

Self-supervised speech representation learningexemplar

Identity

Developer
Meta
Family
not in the notes
Released
19 Dec 2023 sourcesregistry date
Weights published
19 Dec 2023
Record checked
11 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
other Conformer-based W2v-BERT 2.0 speech encoder; bare checkpoint without a task head
Total parameters
600M sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
audio
Output
not in the notes
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
open weights permissive
Licence
MIT License sources
Access routes
open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
not in the notes
Footprint
not in the notes
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
listed by developer
Regional languages
Javanese
Jakarta hosting
unknown
Languages
Pre-trained on 4.5M hours of unlabelled audio in more than 143 languages; card tags include Indonesian, Javanese, Malay, Tagalog, Thai and Vietnamese
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Lineage

The notes record no lineage for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. huggingface.co/facebook/w2v-bert-2.0 https://huggingface.co/facebook/w2v-bert-2.0
  2. huggingface.co/api/models/facebook/w2v-bert-2.0 https://huggingface.co/api/models/facebook/w2v-bert-2.0

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "w2v-Bert-2.0", https://aurion.semai.id/models/meta-w2v-bert-2-0/, records of October 2026.