Paraphrase-multilingual-MiniLM-L12-v2, Table Transformer Detection, and Bielik-11B-v3.0-Instruct are now available in Amazon SageMaker JumpStart

Today, AWS announced the availability of paraphrase-multilingual-MiniLM-L12-v2, Microsoft Table Transformer Detection, and Bielik-11B-v3.0-Instruct in Amazon SageMaker JumpStart.

Paraphrase-multilingual-MiniLM-L12-v2 from Sentence Transformers is a lightweight semantic similarity model that maps sentences and paragraphs to a 384-dimensional dense vector space across 50+ languages. It is well suited for finding semantically similar content within and across languages, making it ideal for cross-lingual semantic search, multilingual document clustering, and sentence similarity scoring without requiring language-specific configuration.

Microsoft Table Transformer Detection is a DETR-based object detection model trained on the PubTables-1M dataset, purpose-built for detecting tables in unstructured documents such as PDFs and scanned images. It is well suited for document digitization pipelines and automated data extraction workflows that require reliably locating tabular content at scale across research papers, financial reports, and other document types.

Bielik-11B-v3.0-Instruct is an 11-billion-parameter generative language model developed by SpeakLeash and ACK Cyfronet AGH, trained on multilingual corpora spanning 32 European languages with a strong emphasis on Polish. It excels at Polish and European language dialogue, STEM and mathematical reasoning, logic and tool-use tasks, and enterprise applications requiring deep linguistic understanding across European languages.

With SageMaker JumpStart, customers can deploy any of these models with just a few clicks to address their specific AI use cases. To get started with these models, navigate to the Models section of SageMaker Studio or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the Amazon SageMaker JumpStart documentation.