Meta-Llama-3.1-8B-Instruct
About Meta-Llama-3.1-8B-Instruct
Meta Llama 3.1 is a family of multilingual large language models developed by Meta, featuring pretrained and instruction-tuned variants in 8B, 70B, and 405B parameter sizes. This 8B instruction-tuned model is optimized for multilingual dialogue use cases and outperforms many available open-source and closed chat models on common industry benchmarks. The model was trained on over 15 trillion tokens of publicly available data, using techniques like supervised fine-tuning and reinforcement learning with human feedback to enhance helpfulness and safety. Llama 3.1 supports text and code generation, with a knowledge cutoff of December 2023
Discover how Meta-Llama-3.1-8B-Instruct's multilingual, instruction-tuned capabilities and extensive context window can solve diverse real-world challenges.
Multilingual Content Creation
Generate culturally relevant content in multiple languages for global audiences, from marketing copy to technical documentation.
Use Case Example:
"Drafted a product launch campaign, creating ad copy and social media posts in English, Spanish, and German, tailored for each region."
Advanced Customer Support
Power AI assistants to understand complex queries and long conversation histories (33K context), delivering accurate, personalized, multilingual support.
Use Case Example:
"Resolved a multi-turn customer issue by analyzing a 15-page chat log, providing a detailed solution and follow-up steps in the user's preferred language."
Code Generation & Refactoring
Quickly generate code snippets, implement features, or refactor existing code across languages from natural language prompts.
Use Case Example:
"Developed a Go microservice endpoint, including API routing and database integration, based on a detailed functional specification, accelerating development."
Contextual Q&A & Summarization
Extract precise answers and summarize key information from extensive documents, manuals, or internal knowledge bases using its large context window.
Use Case Example:
"Answered specific questions about a complex legal contract by analyzing its 40-page text, highlighting relevant clauses and summarizing obligations for a client."
Metadata
Specification
State
Deprecated
Architecture
Transformer Decoder
Calibrated
Yes
Mixture of Experts
No
Total Parameters
8B
Activated Parameters
8B
Reasoning
No
Precision
FP8
Context length
33K
Max Tokens
4K
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