NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices now available in Amazon SageMaker JumpStart
Machine Learning Blog
AWS and NVIDIA have announced the availability of NeMo Retriever Llama 3.2 text embedding and reranking NVIDIA NIM microservices in Amazon SageMaker JumpStart, offering powerful multilingual AI capabilities for enterprise search and retrieval systems.
- Two new microservices are now available: text embedding and text reranking NIM
- Supports 26 languages with document support up to 8,192 tokens
- Reduces data storage footprint by 35-fold through dynamic embedding sizing
- Enables deployment through SageMaker Studio or programmatically via SDK
- Supports real-time and batch inference for various use cases
These models are particularly valuable for enterprise knowledge bases, customer support systems, and multilingual content recommendation engines, providing efficient and accurate semantic search capabilities across diverse languages.
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