ContainersNVIDIADeepSeek-R1NVIDIALlama-3.1-Nemotron-70B-InstructNVIDIAPyTorch
CollectionsNVIDIAOmniverse Kit (FB)NVIDIADeepStream SDKNVIDIAOmniverse Kit App Streaming
ModelsNVIDIAStyleGAN3 pretrained modelsNVIDIAPeopleNetNVIDIATrafficCamNet
ResourcesNVIDIARiva Skills Quick Start
Helm ChartsNVIDIAGPU OperatorNVIDIANVIDIA NIM Operator
NVIDIA
NVIDIA
Llama 3.2 NeMo Retriever Embedding 1B
Model
NVIDIA
NVIDIA
Llama 3.2 NeMo Retriever Embedding 1B

World-class multilingual and cross-lingual question-answering retrieval.

NVIDIA AI Enterprise Supported
This model is backed by NVIDIA's Plus Plus (++) Promise
to learn more about the quality of the datasets used to train this model.
FieldResponse
Intended Application & Domain:Passage and query embedding for question and answer retrieval
Model Type:Transformer encoder
Intended User:Generative AI creators working with conversational AI models - users who want to build a multilingual question and answer application over a large text corpus, leveraging the latest dense retrieval technologies.
Output:Array of float numbers (Dense Vector Representation for the input text)
Describe how the model works:Model transforms the tokenized input text into a dense vector representation.
Performance Metrics:Accuracy, Throughput, and Latency
Potential Known Risks:This model does not always guarantee to retrieve the correct passage(s) for a given query.
Licensing & Terms of Use:The use of this model is governed by the NVIDIA AI Foundation Models Community License Agreement and Llama 3.2 is licensed under the Llama 3.2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
Technical LimitationsThe model’s max sequence length is 8192. Therefore, the longer text inputs should be truncated.
Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of:N/A
Verified to have met prescribed NVIDIA quality standards:Yes