Overview

Meta Llama 3.1 70B Instruct is a 70 billion parameter instruction-tuned large language model developed by Meta. It is part of the Llama 3.1 collection, optimized for multilingual dialogue and general text generation tasks. The model leverages an optimized transformer architecture, supervised fine-tuning (SFT), and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. It was trained on over 15 trillion tokens of publicly available online data with a knowledge cutoff of December 2023, and features a substantial 128k token context length.

Key Capabilities

Multilingual Support: Optimized for English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, with potential for fine-tuning in other languages.
Instruction Following: Highly capable in assistant-like chat scenarios due to extensive instruction tuning.
Tool Use: Supports multiple tool use formats, enabling integration with external functions and services.
Performance: Demonstrates strong performance across various benchmarks, including MMLU (83.6%), HumanEval (80.5% pass@1), GSM-8K (95.1%), and API-Bank (90.0%).
Scalability: Utilizes Grouped-Query Attention (GQA) for improved inference scalability.

Good For

Commercial and Research Applications: Intended for a wide range of commercial and research uses, particularly in multilingual contexts.
Assistant-like Chatbots: Excels in conversational AI applications requiring high-quality, helpful, and safe responses.
Code Generation and Tool Integration: Strong capabilities in code-related tasks and seamless integration with external tools and APIs.
Synthetic Data Generation: Can be used to improve other models through synthetic data generation and distillation.