Meta-Llama-3.1-70B-Instruct
Maintainer: meta-llama
393
🖼️
| 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 Meta-Llama-3.1-70B is a part of the Meta Llama 3.1 collection of multilingual large language models (LLMs) developed by Meta. This 70B parameter model is a pretrained and instruction-tuned generative model that supports text input and text output in multiple languages, including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. It was trained on a new mix of publicly available online data and utilizes an optimized transformer architecture.
Similar models in the Llama 3.1 family include the Meta-Llama-3.1-8B and Meta-Llama-3.1-405B, which vary in their parameter counts and performance characteristics. All Llama 3.1 models use Grouped-Query Attention (GQA) for improved inference scalability.
Model inputs and outputs
Inputs
- Multilingual Text: The
Meta-Llama-3.1-70Bmodel accepts text input in any of the 8 supported languages. - Multilingual Code: In addition to natural language, the model can also process code snippets in various programming languages.
Outputs
- Multilingual Text: The model can generate text output in any of the 8 supported languages.
- Multilingual Code: The model is capable of producing code output in addition to natural language.
Capabilities
The Meta-Llama-3.1-70B model is designed for a variety of natural language generation tasks, including assistant-like chat, translation, and even code generation. Its strong performance on industry benchmarks across general knowledge, reasoning, reading comprehension, and other domains demonstrates its broad capabilities.
What can I use it for?
The Meta-Llama-3.1-70B model is intended for commercial and research use in multiple languages. Developers can leverage its text generation abilities to build chatbots, virtual assistants, and other language-based applications. The model's versatility also allows it to be adapted for tasks like content creation, text summarization, and even data augmentation through synthetic data generation.
Things to try
One interesting aspect of the Meta-Llama-3.1-70B model is its ability to handle multilingual inputs and outputs. Developers can experiment with using the model to translate between the supported languages, or to generate text that seamlessly incorporates multiple languages. Additionally, the model's strong performance on coding-related benchmarks suggests that it could be a valuable tool for building code-generating assistants or integrating code generation capabilities into various applications.
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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