nvidia/NV-Embed-v2
feature-extraction model by nvidia
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Model card & documentation
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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)(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. NV-Embed-v2 presents several new designs, including having the LLM attend to latent vectors for better pooled embedding output, and demonstrating a two-staged instruction tuning method to enhance the accuracy of both retrieval and non-retrieval tasks. Additionally, NV-Embed-v2 incorporates a novel hard-negative mining methods that take into account the positive relevance score for better false negatives removal. For more technical details, refer to our paper: NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models. Here is an example of how to encode queries and passages using Huggingface-transformer and…
Read the full model card ↗ · Preview checked 2026-10-28T18:25:09.100Z
Inside the original model card — Document outline
- Introduction
- Model Details
- How to use
- Usage (HuggingFace Transformers)
- Usage (Sentence-Transformers)
- License
- Correspondence to
- Citation
- Troubleshooting
- 1. Instruction template for MTEB benchmarks
- 2. Required Packages
- 3. How to enable Multi-GPU (Note, this is the case for HuggingFace Transformers)
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Model overview
nvidia/NV-Embed-v2 is a feature-extraction model repository published by nvidia on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- feature-extraction
- Library
- transformers
- Recent downloads (30 days)
- 310,254
- Cumulative likes
- 524
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 7,851,016,192
- Architecture
- NVEmbedModel
- License
- cc-by-nc-4.0
- Access
- Not gated by Hugging Face
- Created
- 2024-08-29T13:00:32.000Z
- Last modified
- 2025-07-21T17:48:20.000Z
Compatibility and lineage
Reported languages: en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:29.511Z. Daily imports are snapshots, not real-time monitoring.
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