What is NVIDIA NIM? How to Use It?

Nvidia launches NIM to make it smoother to deploy AI models into production


NVIDIA NIM (NVIDIA Inference Microservices) is a set of easy-to-use microservices for accelerating the deployment of foundation models on any cloud or data center infrastructure. It is designed to optimize AI infrastructure for maximum efficiency and cost-effectiveness, while also reducing hardware and operational costs. NVIDIA NIM packages domain-specific NVIDIA CUDA libraries and specialized code tailored to various domains such as language, speech, video processing, and generative biology chemistry.

NVIDIA NIM's Key Features

Here's a breakdown of NIM's key features:

Simplified deployment : NIM streamlines the deployment process by automatically containerizing models and optimizing them for NVIDIA hardware. This eliminates the need for manual configuration and ensures efficient resource utilization.

Scalability : NIM can manage and scale deployments across multiple NVIDIA platforms, including on-premises, cloud, and edge environments. This allows you to easily adapt to changing workloads and data requirements.

Monitoring and management : NIM provides comprehensive tools for monitoring model performance, resource utilization, and health. This enables you to identify and troubleshoot issues quickly and optimize your deployments for maximum efficiency.

Security : NIM offers robust security features to protect your models and data. This includes support for encryption, authentication, and authorization.

How to Use NVIDIA NIM?

To use NVIDIA NIM, developers can follow these steps:

Access AI models in NVIDIA API catalog : Developers can access a wide range of AI models in the NVIDIA API catalog, which can be used to build and deploy their own AI applications. They can begin prototyping directly in the catalog using the graphical user interface or interact directly with the API for free.

Sign up for NVIDIA AI Enterprise evaluation license : To deploy the microservice on their infrastructure, developers need to sign up for the NVIDIA AI Enterprise 90-day evaluation license.

Download the model : Developers can download the model they want to deploy from NVIDIA NGC. For example, they can download a version of the Llama-2 7B model built for a single A100 GPU using the following command: `ngc registry model download-version "ohlfw0olaadg/ea-participants/llama-2-7b:LLAMA-2-7B-4K-FP16-1-A100.24.01"`.

Unpack the downloaded artifact : Developers can unpack the downloaded artifact into a model repository using the following command: `tar -xzf llama-2-7b_vLLAMA-2-7B-4K-FP16-1-A100.24.01/LLAMA-2-7B-4K-FP16-1-A100.24.01.tar.gz`.

Deploy the microservice : Developers can deploy the microservice on their infrastructure using the NVIDIA AI Enterprise 90-day evaluation license.

NVIDIA NIM also provides microservices for model customization across different domains, enabling businesses to optimize their AI infrastructure for maximum efficiency and cost-effectiveness without worrying about AI model performance and scalability. NVIDIA NeMo offers fine-tuning capabilities using proprietary data for LLMs, speech AI, and multimodal models. NVIDIA BioNeMo accelerates drug discovery with a growing collection of models for generative biology chemistry, and molecular prediction. NVIDIA Picasso enables faster creative workflows with Edify models. These models are trained on licensed libraries from visual content providers, enabling the deployment of customized generative AI models for visual content creation.

Resources for Learning More about NVIDIA NIM

Here are some resources to help you learn more about NVIDIA NIM:

NVIDIA API Documentation: https://docs.api.nvidia.com/

Instantly Run and Deploy Generative AI: https://www.nvidia.com/en-us/ai/