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Use when searching, extracting, ingesting, or querying a document collection with the NeMo Retriever 26.8.1 CLI, including local LanceDB indexes and deployed Retriever services. Use for PDFs, images, Office files, HTML, text, audio, and video; not for edi Multimodal question-answer retrieval representing user queries as text and documents as images.Downloadablellama-nemotron-embed-vl-1b-v2
GPU-accelerated model optimized for providing a probability score that a given passage contains the information to answer a question.Downloadablellama-nemotron-rerank-vl-1b-v2
Nemotron OCR v2 is a state-of-the-art multilingual text recognition model designed for robust end-to-end optical character recognition (OCR) on complex real-world images.Downloadablenemotron-ocr-v2
Powerful OCR model for fast, accurate real-world image text extraction, layout, and structure analysis.Downloadablenemoretriever-ocr
Powerful OCR model for fast, accurate real-world image text extraction, layout, and structure analysis.Downloadablenemotron-ocr-v1
Model for object detection, fine-tuned to detect charts, tables, and titles in documents.Downloadablenemotron-graphic-elements-v1
Model for object detection, fine-tuned to detect charts, tables, and titles in documents.Downloadablenemotron-table-structure-v1
Power fast, accurate semantic search across multimodal enterprise data with NVIDIA’s RAG Blueprint—built on NeMo Retriever and Nemotron models—to connect your agents to trusted, authoritative sources of knowledge.GeneralLaunchableDeveloper ExampleBuild a RAG Pipeline Blueprint
An AI-powered, multi-agent system designed to optimize warehouse operations through intelligent automation, real-time monitoring, and natural language interaction.RetailLaunchableDeveloper ExampleMulti-Agent Intelligent Warehouse
Elevate Shopping Experiences Online and In Stores.RetailLaunchableDeveloper ExampleRetail Shopping Assistant
Sensor-captured radio enables real-time awareness, AI-driven analytics for actionable, searchable insights.MediaLaunchableDeveloper ExampleStreaming Data to RAG
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