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Llama 3.1 Nemotron 70B Instruct AWQ INT4

Developed by joshmiller656
A large language model with 70 billion parameters customized by NVIDIA, optimized through AWQ Int4 quantization, and performs excellently in multiple automatic alignment benchmark tests.
Downloads 1,591
Release Time : 10/29/2024

Model Overview

An instruction fine-tuning model designed to improve the effectiveness of large language model responses, supporting multilingual interaction.

Model Features

High-performance quantization
Adopts AWQ Int4 quantization technology to significantly reduce resource requirements while maintaining model performance.
Multilingual support
Supports text generation and understanding in 8 mainstream languages.
Instruction optimization
Significantly improves the response quality to user queries through NVIDIA customization and optimization.
Benchmark leading
Surpasses GPT - 4o and Claude 3.5 in benchmark tests such as Arena Hard, AlpacaEval 2 LC, and MT Bench.

Model Capabilities

Multi - turn dialogue generation
Multilingual text understanding
Complex instruction following
Long text generation (up to 4k tokens)
Context - aware response

Use Cases

Intelligent assistant
Question - answering system
Answer various knowledge - based questions from users.
Performs excellently in fact - accuracy benchmark tests.
Content generation
Multilingual content creation
Generate marketing copy or creative content in multiple languages.
Supports smooth generation in 8 languages.
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