nvidia/llama-3.1-nemotron-70b-instruct

Model Overview

Description:

Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.

This model is ready for commercial use.

Terms of use

By accessing this model, you are agreeing to the LLama 3 terms and conditions of the license, acceptable use policy and Meta’s privacy policy

References(s):

• HelpSteer2-Preference
• SteerLM method
• HelpSteer
• HelpSteer2
• Introducing Llama 3.1: Our most capable models to date
• Meta's Llama 3.1 Webpage
• Meta's Llama 3.1 Model Card

Model Architecture:

Architecture Type: Transformer
Network Architecture: Llama 3.1

Input:

Input Type(s): Text
Input Format: String
Input Parameters: One Dimensional (1D)
Other Properties Related to Input: Max of 128k tokens

Output:

Output Type(s): Text
Output Format: String
Output Parameters: One Dimensional (1D)
Other Properties Related to Output: Max of 4k tokens

Software Integration:

Supported Hardware Microarchitecture Compatibility:

• NVIDIA Ampere
  
• NVIDIA Hopper
  
• NVIDIA Turing
  Supported Operating System(s): Linux
  

Model Version:

v1.0

Training & Evaluation:

Datasets:

Data Collection Method by dataset

• [Hybrid: Human, Synthetic]
  

Labeling Method by dataset

• [Human]
  

Link:

• HelpSteer2

Properties (Quantity, Dataset Descriptions, Sensor(s)):

• 21, 362 prompt-responses built to make more models more aligned with human preference - specifically more helpful, factually-correct, coherent, and customizable based on complexity and verbosity.
• 20, 324 prompt-responses used for training and 1, 038 used for validation.

Inference:

Engine: Triton
Test Hardware: H100, A100 80GB, A100 40GB

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety & Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns here.

Please report security vulnerabilities or NVIDIA AI Concerns here.