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Llama-3.1-8B-Instruct

Llama 3.1-8B-Instruct is Meta's 8-billion-parameter instruction-tuned model, supporting 8 languages including English, German, French, Spanish, Italian, Portuguese, Hindi, and Thai. Released under the Llama 3.1 license (permissive with restrictions for products over 700M users), it was a leading open-weight model at its scale at release. Context window extends to 128K tokens.

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Fields below are copied from the tags and counters on the HuggingFace repository meta-llama/Llama-3.1-8B-Instruct at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.

Publisher (HF namespace)
meta-llama
Pipeline tag
text-generation
Library
Transformers
Framework tags
PyTorch
Weight formats
safetensors
License tag
llama3.1 — read the license file in the repo before relying on it
Lineage
Language tags
English (en), German (de), French (fr), Italian (it), Portuguese (pt), Hindi (hi), Spanish (es), Thai (th)
Papers cited
arXiv:2204.05149
Downloads (HF counter at last fetch)
5,644,341
Likes (HF counter at last fetch)
6,771
Model card
https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct

Use cases

  • Multilingual instruction following across 8 supported languages
  • Long-context document analysis using the 128K token context window
  • Local LLM deployment on consumer GPUs for general-purpose tasks
  • RAG pipeline generation component with strong reading comprehension
  • Code generation and explanation in common programming languages

Pros

  • 128K token context window enables long document analysis
  • 8-language support including Hindi and Thai beyond standard OECD languages
  • Widely benchmarked with established performance baselines
  • Text-generation-inference compatible; active community fine-tunes available

Cons

  • Llama 3.1 license restricts use by products/services over 700M monthly users
  • Llama 3.1 is superseded by Llama 3.2 and 3.3 in Meta's family
  • 16-24GB VRAM at FP16; quantization required for consumer GPUs under 16GB
  • 8B scale limits complex multi-step reasoning accuracy vs. 13B+ models
  • Supported languages are 8 specific ones — other languages have degraded performance

Tags

transformerssafetensorsllamatext-generationfacebookmetapytorchllama-3conversationalendefritpthiestharxiv:2204.05149base_model:meta-llama/Llama-3.1-8Bbase_model:finetune:meta-llama/Llama-3.1-8B