LLMfamily
Cendol
IndoNLP's instruction-tuned mT5 (small to XXL) and Llama 2 (7B, 13B) models for Indonesian and local languages.
Levelfamily
ClassLLM
Parameters13B
Contextnot in the notes
Released21 Apr 2024
Opennessunknown
Runs onconsumer GPU, CPU server
Statusactive
Lineage
finetune
Where this comes from
Parent and child relations from model cards, Hugging Face base_model fields and the genealogy tables of the research notes. The tree shows two generations each way, 4 models. Confidence and evidence are the notes' own.
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
- not in the notes
- Total parameters
- 13B sources
- Active parameters
- –
- Checkpoint parameters
- –
- Note
- 0.3B to 13B
- 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
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- consumer GPU, CPU server
- 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
- not in the notes
- Jakarta hosting
- unknown
- Languages
- Indonesian + local languages
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.
Links
DeveloperIndoNLPopen community, Indonesia
ModelCendolIndoNLP, LLM
R&D TopicsLow-Resource and Regional Language ResourcesOpen Post-Training RecipesRegional 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 4
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 byOpen Post-Training RecipesOpenly released data, code and methods (instruction tuning, preference optimisation, veri…produced by
Sources
- indonlp (IndoNLP) huggingface.co https://huggingface.co/indonlp
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Cendol", https://aurion.semai.id/models/indonlp-cendol/, records of October 2026.