nvidia/llama-nemotron-embed-1b-v2
feature-extraction model by nvidia
From the publisher
Model card & documentation
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The Llama Nemotron Embedding 1B model is optimized for multilingual and cross-lingual text question-answering retrieval with support for long documents (up to 8192 tokens) and dynamic embedding size (Matryoshka Embeddings). This model was evaluated on 26 languages: English, Arabic, Bengali, Chinese, Czech, Danish, Dutch, Finnish, French, German, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Korean, Norwegian, Persian, Polish, Portuguese, Russian, Spanish, Swedish, Thai, and Turkish. In addition to enabling multilingual and cross-lingual question-answering retrieval, this model reduces the data storage footprint by 35x through dynamic embedding sizing and support for longer token length, making it feasible to handle large-scale datasets efficiently. An embedding model is a crucial component of a text retrieval system, as it transforms textual information into dense vector representations. They are typically transformer encoders that process tokens of input text (for example: question, passage) to output an embedding. This model is ready for commercial use. The Llama Nemotron…
Read the full model card ↗ · Preview checked 2026-10-31T08:43:24.421Z
Inside the original model card — Document outline
- Model Overview
- Description
- Intended use
- License/Terms of use
- Model Architecture
- Input
- Output
- Installation
- Sentence Transformers Usage
- Transformers Usage
- vLLM Usage
- Software Integration
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Model overview
nvidia/llama-nemotron-embed-1b-v2 is a feature-extraction model repository published by nvidia on Hugging Face. The source reports the sentence-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
- sentence-transformers
- Recent downloads (30 days)
- 338,481
- Cumulative likes
- 72
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 1,235,814,400
- Architecture
- LlamaBidirectionalModel
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2025-10-16T22:44:33.000Z
- Last modified
- 2026-05-20T18:24:18.000Z
Compatibility and lineage
Reported languages: multilingual
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.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.