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Text Embedding NIM

NeMo Retriever Text Embedding NIM (Text Embedding NIM) brings the power of state-of-the-art text embedding models to your applications, offering unparalleled natural language processing and understanding capabilities. You can use Text Retriever NIM for semantic search, Retrieval Augmented Generation (RAG) pipelines—or any application that uses text embeddings. Text Embedding NIM is built on the NVIDIA software platform, incorporating CUDA, TensorRT, and Triton to offer out-of-the-box GPU acceleration.

Getting started with the NIM

Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more.

Security Vulnerabilities in Open Source Packages

Please review the Security Scanning tab to view the latest security scan results.

For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Get Help

NVIDIA Developer Community Forum

For support, Visit the NVIDIA Developer Community Forum

Governing Terms

The NIM container is governed by NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement and NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product; and the use of this model is governed by the ai-foundation-models-community-license.pdf.

Additional information: Apache license.

You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.

End of Support — \"This artifact is no longer supported. NVIDIA strongly recommends artifacts that are up to date and supported\"

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You can use Text Retriever NIM for semantic search, [Retrieval Augmented Generation (RAG) ](https://blogs.nvidia.com/blog/what-is-retrieval-augmented-generation/)pipelines—or any application that uses text embeddings. Text Embedding NIM is built on the NVIDIA software platform, incorporating CUDA, TensorRT, and Triton to offer out-of-the-box GPU acceleration.\n\n## Getting started with the NIM\n\nDeploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the [NIM Container](https://docs.nvidia.com/nim/nemo-retriever/text-embedding/latest/overview.html) page for release documentation, deployment guides and more.\n\n## Security Vulnerabilities in Open Source Packages\n\nPlease review the Security Scanning tab to view the latest security scan results.\n\nFor certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.\n\n## Get Help\n\n### NVIDIA Developer Community Forum\n\nFor support, Visit the [NVIDIA Developer Community Forum](https://forums.developer.nvidia.com/)\n\n## Governing Terms\n\nThe NIM container is governed by [NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); and the use of this model is governed by the [ai-foundation-models-community-license.pdf](https://docs.nvidia.com/ai-foundation-models-community-license.pdf).\n\nAdditional information: [Apache license](https://choosealicense.com/licenses/apache-2.0/).\n\n**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**\n\n**End of Support** — \"This artifact is no longer supported. 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The information collected might relate to you, your preferences, or your device. We use that information to make the site work, analyze performance and traffic on our website, provide a more personalized web experience, and assist in our marketing efforts.

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