Llama-3.1-8B-Instruct
Maintainer: meta-llama
2.7K
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The Llama-3.1-8B-Instruct model is part of the Meta Llama 3.1 collection of multilingual large language models (LLMs). This collection includes pretrained and instruction tuned generative models in 8B, 70B, and 405B sizes, with the instruction tuned text-only models designed for multilingual dialogue use cases. The Llama-3.1-405B-Instruct and Llama-3.1-70B-Instruct are other models in this collection. These models outperform many available open-source and closed-chat models on common industry benchmarks.
Model inputs and outputs
Inputs
- Multilingual text
Outputs
- Multilingual text and code
Capabilities
The Llama-3.1-8B-Instruct model is an autoregressive language model that uses an optimized transformer architecture. The instruction tuned versions, like this one, employ supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align the model with human preferences for helpfulness and safety.
What can I use it for?
The Llama-3.1-8B-Instruct model is intended for commercial and research use in multiple languages. The instruction tuned text-only models are designed for assistant-like chat applications, while the pretrained models can be adapted for a variety of natural language generation tasks. The Llama 3.1 model collection also supports using the outputs to improve other models, such as through synthetic data generation and distillation.
Things to try
Developers can fine-tune the Llama-3.1-8B-Instruct model for additional languages beyond the 8 supported, as long as they comply with the Llama 3.1 Community License and Acceptable Use Policy. However, it's important to ensure any use in non-supported languages is done in a safe and responsible manner.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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