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Llama-4-Scout-17B-16E-Instruct

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AI ModelsAI Models & LLMsOpen source · Web

Llama-4-Scout-17B-16E-Instruct is a multimodal AI model designed by Meta. It leverages a mixture-of-experts architecture to provide advanced text and image understanding capabilities, supporting multilingual outputs and fine-tuning for diverse applications.

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Description

Llama-4-Scout-17B-16E-Instruct is part of the Llama 4 series by Meta, designed to advance AI through open source and open science. This model is a 17 billion parameter AI with 16 experts, utilizing a mixture-of-experts architecture for enhanced performance in text and image understanding. It supports multilingual text and code outputs, making it versatile for various applications.

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The model is trained on a mix of publicly available and licensed data, including interactions from Meta's platforms like Instagram and Facebook. It is intended for commercial and research use, optimized for tasks such as visual recognition, image reasoning, and natural language generation. The model's training data has a cutoff of August 2024, ensuring it is up-to-date with recent information.

Llama-4-Scout-17B-16E-Instruct is released under the Llama 4 Community License Agreement, which allows for commercial use with certain conditions. The model is designed to be safe and flexible, with safeguards in place to prevent misuse. It has been tested for image understanding with up to five input images, and developers are encouraged to perform additional testing for specific applications.

Meta has focused on reducing model refusals to benign prompts and improving the model's tone to sound more natural. The model is also more steerable, allowing developers to tailor responses to specific needs. Llama-4-Scout-17B-16E-Instruct is a powerful tool for developers looking to leverage AI for a wide range of applications, from chatbots to visual QA.

  • CategoryAI Models & LLMs
  • Pricing ModelOpen source
  • DeploymentCloud
  • PlatformsWeb

Llama-4-Scout-17B-16E-Instruct Highlights

  • Mixture-of-experts architecture

  • Multimodal AI model

  • 17 billion parameters

  • Supports multilingual text and code

  • Fine-tuning capabilities

  • Trained on publicly available and licensed data

  • Optimized for visual recognition and reasoning

  • Released under Llama 4 Community License

Getting Started with Llama-4-Scout-17B-16E-Instruct

  1. Access page: Visit the model's page on Hugging Face

  2. Load model: Use the Hugging Face Transformers library

  3. Configure environment: Ensure compatibility with transformers v4.51.0

  4. Integrate: Incorporate the model into your application

  5. Fine-tune: Adjust the model for specific tasks

Llama-4-Scout-17B-16E-Instruct's Use Cases

  • Visual Recognition
  • Image Reasoning
  • Multilingual Chatbots
  • Natural Language Generation
  • Code Generation

FAQ from Llama-4-Scout-17B-16E-Instruct

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