LLM
ViT5 base
T5-style encoder-decoder pre-trained on Vietnamese text, for Vietnamese summarisation and generation.
Levelmodel
ClassLLM
Parametersnot in the notes
Contextnot in the notes
Released14 Mar 2022
Opennessopen weights permissive
Runs onnot in the notes
Statusactive
R&D Topics
Identity
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
- 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
- not stated
- Regional languages
- Vietnamese
- Jakarta hosting
- unknown
- Languages
- 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.
Links
DeveloperVietAIopen community
VietAIopen communityModelViT5 baseVietAI, LLM
ViT5 baseVietAI, LLMR&D TopicsLow-Resource and Regional Language ResourcesRegional or National Foundation Model Training (Continued Pretraining at 7B to 70B)Text-to-Text Pretraining and Summarisation
Use CasesIndonesian and Regional-Language LLMsPublic SectorIndonesian NLU (Classification, NER)Public SectorBanking Customer Service AssistantsFinanceCitizen Service AssistantsPublic Sector+5 moreUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
PT Bank Tabungan Negara (BTN)In production, 1 Jul 2026
PT PegadaianIn production, 5 Jun 2026
Bank Central Asia (BCA)In production, 16 Mar 2026Bank Central Asia (BCA)In production, 16 Mar 2026+13 moreDeployments of these use cases; none names this model.
PT Bank Tabungan Negara (BTN)In production, 1 Jul 2026PT PegadaianIn production, 5 Jun 2026Bank Central Asia (BCA)In production, 16 Mar 2026Bank Central Asia (BCA)In production, 16 Mar 2026+13 moreDeployments of these use cases; none names this model.Organisations 1
R&D topics 3
Regional or National Foundation Model Training (Continued Pretraining at 7B to 70B)Pretraining or continued pretraining a mid-size model to serve a national or regional lan…produced byLow-Resource and Regional Language ResourcesDatasets, benchmarks and adaptation for under-served languages.produced byText-to-Text Pretraining and SummarisationEncoder-decoder models pretrained to map any text task to text, with objectives tailored…produced by
Sources
- huggingface.co/VietAI/vit5-base https://huggingface.co/VietAI/vit5-base
- huggingface.co/api/models?pipeline_tag=question-answering&so... https://huggingface.co/api/models?pipeline_tag=question-answering&sort=downloads&limit=50
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "ViT5 Base", https://aurion.semai.id/models/vietai-vit5-base/, records of October 2026.