embedding

paraphrase-multilingual-MiniLM-L12-v2

A multilingual sentence-transformers model mapping sentences and paragraphs to a 384-dimensional vector for clustering and semantic search.

Sentence Transformers

Levelmodel

Classembedding

Parameters117.65M

Context128

Released2 Mar 2022

Opennessopen weights permissive

Runs onnot in the notes

Statusnot in the notes

R&D Topics

Retrieval-augmented generation (RAG)used by Text embeddings for semantic searchproduced by

Identity

Developer: Sentence Transformers
Family: not in the notes
Released: 2 Mar 2022 sourcesregistry date
Weights published: 2 Mar 2022
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 BertModel transformer with mean pooling to a 384-dimensional vector
Total parameters: 117.65M sources
Active parameters: –
Checkpoint parameters: –
Note: Hugging Face API Safetensors count
Context length: 128 tokens
Input: text
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: Apache License 2.0 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: not in the notes
Jakarta hosting: unknown
Languages: Card language tags list about 50 languages including Indonesian, Malay, 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.

Links

Developer

Sentence Transformersopen community

Model

paraphrase-multilingual-MiniLM-L12-v2Sentence Transformers, embedding

R&D TopicsRetrieval-Augmented Generation (RAG)Text Embeddings for Semantic Search

Use CasesEmbeddings and Retrieval for SEA LanguagesPublic SectorUse cases of models in the same R&D topic; none is recorded for this model itself.

Who Runs Itnone recordedDeployments of these use cases; none names this model.

Graph

Organisations 1

Sentence Transformersopen communityDeveloper

R&D topics 2

Retrieval-Augmented Generation (RAG)Grounding generation in retrieved documents.used by Text Embeddings for Semantic SearchTraining encoders that turn text in many languages into vectors so that search, clusterin…produced by

Sources

huggingface.co/sentence-transformers/paraphrase-multilingual... https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
huggingface.co/api/models/sentence-transformers/paraphrase-m... https://huggingface.co/api/models/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Paraphrase-Multilingual-MiniLM-L12-v2", https://aurion.semai.id/models/sentence-transformers-paraphrase-multilingual-minilm-l12-v2/, records of October 2026.