NousResearch/Meta-Llama-3.1-8B
Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Jul 24, 2024License:llama3.1Architecture:Transformer0.0K Warm

NousResearch/Meta-Llama-3.1-8B is an 8 billion parameter instruction-tuned generative language model developed by Meta, part of the Llama 3.1 collection. Optimized for multilingual dialogue use cases, it features a 128k context length and is trained on over 15 trillion tokens of diverse online data with a December 2023 cutoff. This model excels in assistant-like chat applications and supports commercial and research use across multiple languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.

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Overview

Meta-Llama-3.1-8B is an 8 billion parameter instruction-tuned model from Meta's Llama 3.1 family, designed for multilingual dialogue. It utilizes an optimized transformer architecture and is fine-tuned using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety. The model boasts a substantial 128k context length and was trained on over 15 trillion tokens of publicly available online data, with a knowledge cutoff of December 2023.

Key Capabilities

  • Multilingual Support: Optimized for English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, with potential for fine-tuning in other languages.
  • Enhanced Performance: Instruction-tuned versions show improvements across various benchmarks, including MMLU, IFEval, HumanEval, and MATH, compared to Llama 3 8B Instruct.
  • Tool Use: Demonstrates significant advancements in tool-use benchmarks like API-Bank and BFCL.
  • Long Context Window: Features a 128k token context length, enabling processing of extensive inputs.

Good For

  • Assistant-like Chat: Ideal for building conversational AI applications and chatbots.
  • Multilingual Applications: Suitable for commercial and research use cases requiring multilingual text generation and understanding.
  • Code Generation: Shows strong performance in coding benchmarks like HumanEval and MBPP++.
  • Reasoning and Math: Improved capabilities in complex reasoning and mathematical problem-solving tasks.
Popular Sampler Settings

Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.

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