Hugging Face Overview
Overview
ByteResearch/Llama-3-8B-Instruct is an 8 billion parameter instruction-tuned model from Meta's Llama 3 family. It is built on an optimized transformer architecture, incorporating Grouped-Query Attention (GQA) for enhanced inference scalability. The model was pretrained on an extensive dataset of over 15 trillion tokens from publicly available sources, with instruction tuning further refined using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Key Capabilities
- Optimized for Dialogue: Specifically designed for assistant-like chat applications.
- Strong Benchmark Performance: Demonstrates significant improvements over Llama 2 models across various benchmarks, including MMLU (68.4), HumanEval (62.2), and GSM-8K (79.6).
- Robust Training: Benefits from a massive pretraining dataset and advanced fine-tuning techniques.
- English Language Focus: Primarily intended for commercial and research use in English.
Good For
- Developing conversational AI agents and chatbots.
- Research in natural language generation and understanding.
- Applications requiring strong reasoning and problem-solving capabilities, as indicated by its benchmark scores.
- Developers seeking a powerful, open-source instruction-tuned model for English-based tasks.