Task
Feature Extraction
G
ibm-granite/granite-embedding-97m-multilingual-r2
Feature Extraction·ibm-granite· 200.3K· 123
Model Summary: Granite-Embedding-97M-Multilingual-R2 is a 97M parameter dense embedding model from the Granite Embeddings collection for high-quality multilingual text embeddings at minimal compute cost. It produces 384-dimensional vectors with a context length of up to 32,768 tokens. The model supports 200+ languages (based on the multilingual pretraining corpus of the underlying encoder), with e
# pull & run locally
pip install mlforge-sdk && mlforge pull ibm-granite/granite-embedding-97m-multilingual-r2
pip install mlforge-sdk && mlforge pull ibm-granite/granite-embedding-97m-multilingual-r2
Model details
Provider
ibm-granite
Framework
sentence-transformers
Parameters
97.4M
Size
1.1 GB
License
apache-2.0
Downloads
200.3K
Likes
123
Paper
arXiv:2605.13521
Updated
2026-05-18
About ibm-granite/granite-embedding-97m-multilingual-r2
Model Summary: Granite-Embedding-97M-Multilingual-R2 is a 97M parameter dense embedding model from the Granite Embeddings collection for high-quality multilingual text embeddings at minimal compute cost. It produces 384-dimensional vectors with a context length of up to 32,768 tokens. The model supports 200+ languages (based on the multilingual pretraining corpus of the underlying encoder), with enhanced support for 52 languages and programming code that receive explicit retrieval-pair and cross-lingual training. All training data uses permissive, enterprise-friendly licenses, plus IBM-collected and IBM-generated datasets.