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Description
NVIDIA NeMo LLM offers a streamlined approach to personalizing and utilizing large language models that are built on a variety of frameworks. Developers are empowered to implement enterprise AI solutions utilizing NeMo LLM across both private and public cloud environments. They can access Megatron 530B, which is among the largest language models available, via the cloud API or through the LLM service for hands-on experimentation. Users can tailor their selections from a range of NVIDIA or community-supported models that align with their AI application needs. By utilizing prompt learning techniques, they can enhance the quality of responses in just minutes to hours by supplying targeted context for particular use cases. Moreover, the NeMo LLM Service and the cloud API allow users to harness the capabilities of NVIDIA Megatron 530B, ensuring they have access to cutting-edge language processing technology. Additionally, the platform supports models specifically designed for drug discovery, available through both the cloud API and the NVIDIA BioNeMo framework, further expanding the potential applications of this innovative service.
Description
NVIDIA NeMo Retriever is a suite of microservices designed for creating high-accuracy multimodal extraction, reranking, and embedding workflows while ensuring maximum data privacy. It enables rapid, contextually relevant responses for AI applications, including sophisticated retrieval-augmented generation (RAG) and agentic AI processes. Integrated within the NVIDIA NeMo ecosystem and utilizing NVIDIA NIM, NeMo Retriever empowers developers to seamlessly employ these microservices, connecting AI applications to extensive enterprise datasets regardless of their location, while also allowing for tailored adjustments to meet particular needs. This toolset includes essential components for constructing data extraction and information retrieval pipelines, adeptly extracting both structured and unstructured data, such as text, charts, and tables, transforming it into text format, and effectively removing duplicates. Furthermore, a NeMo Retriever embedding NIM processes these data segments into embeddings and stores them in a highly efficient vector database, optimized by NVIDIA cuVS to ensure faster performance and indexing capabilities, ultimately enhancing the overall user experience and operational efficiency. This comprehensive approach allows organizations to harness the full potential of their data while maintaining a strong focus on privacy and precision.
API Access
Has API
API Access
Has API
Integrations
NVIDIA NIM
AI-Q NVIDIA Blueprint
Accenture AI Refinery
Globant Enterprise AI
Linker Vision
NVIDIA AI Data Platform
NVIDIA AI Foundations
NVIDIA Blueprints
NVIDIA FLARE
NVIDIA Llama Nemotron
Integrations
NVIDIA NIM
AI-Q NVIDIA Blueprint
Accenture AI Refinery
Globant Enterprise AI
Linker Vision
NVIDIA AI Data Platform
NVIDIA AI Foundations
NVIDIA Blueprints
NVIDIA FLARE
NVIDIA Llama Nemotron
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
www.nvidia.com/en-us/gpu-cloud/nemo-llm-service/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/nemo-retriever