Project AURIONAI Use-Cases Research & Innovation
LLMfamily

BART

Denoising sequence-to-sequence pre-training that corrupts text and learns to rebuild it, strong for summarisation; the MNLI fine-tune is widely used for zero-shot classification.

MetaMetaUSA
Meta
Levelfamily
ClassLLM
Parametersnot in the notes
Contextnot in the notes
Released29 Oct 2019
Opennessunknown
Runs onnot in the notes
Statusactive

Lineage

Hugging FaceDistilBART CNN 12-6 belongs to this familyLLM24 Oct 2020
MetaBART large belongs to this familyLLM
MetaBART large CNN belongs to this familyLLM406.29M
MetaBART large MNLI belongs to this familylanguage encoder407.34M
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. Confidence and evidence are the notes' own.

R&D Topics

Text-to-text pretraining and summarisationexemplar

Identity

Developer
Meta
Family
not in the notes
Released
29 Oct 2019 sourcesannouncement page
Weights published
–
Record checked
12 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
dense transformer
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
text
Output
text
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
unknown
Licence
not in the notes 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
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
Model card languages: en
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.

Industry Use Cases

No industry use case links this model.

Sources

  1. arxiv.org/abs/1910.13461 https://arxiv.org/abs/1910.13461
  2. github.com/facebookresearch/fairseq/tree/main/examples/b... https://github.com/facebookresearch/fairseq/tree/main/examples/bart
  3. kaggle.com/models/keras/bart https://www.kaggle.com/models/keras/bart
  4. paperswithcode.com/method/bart https://paperswithcode.com/method/bart
  5. huggingface.co/facebook/bart-large https://huggingface.co/facebook/bart-large
  6. huggingface.co/facebook/bart-large-cnn https://huggingface.co/facebook/bart-large-cnn

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "BART", https://aurion.semai.id/models/meta-bart/, records of October 2026.