Update metadata: Add library_name to Transformers
Browse files
README.md
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language:
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- en
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license: cc-by-nc-4.0
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---
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## Introduction
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We present NV-Embed-v2, a generalist embedding model that ranks No. 1 on the Massive Text Embedding Benchmark ([MTEB benchmark](https://huggingface.co/spaces/mteb/leaderboard))(as of Aug 30, 2024) with a score of 72.31 across 56 text embedding tasks. It also holds the No. 1 in the retrieval sub-category (a score of 62.65 across 15 tasks) in the leaderboard, which is essential to the development of RAG technology.
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language:
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- en
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license: cc-by-nc-4.0
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library_name: transformers
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---
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## Introduction
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We present NV-Embed-v2, a generalist embedding model that ranks No. 1 on the Massive Text Embedding Benchmark ([MTEB benchmark](https://huggingface.co/spaces/mteb/leaderboard))(as of Aug 30, 2024) with a score of 72.31 across 56 text embedding tasks. It also holds the No. 1 in the retrieval sub-category (a score of 62.65 across 15 tasks) in the leaderboard, which is essential to the development of RAG technology.
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