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LLaVA

23,501
2,603
Python

Project Description

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

LLaVA: [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyo

Project Title

LLaVA โ€” Visual Instruction Tuning for Large Language and Vision Models

Overview

LLaVA is an open-source project focused on developing large language and vision models with capabilities beyond GPT-4. It aims to provide a robust framework for visual instruction tuning, enabling the creation of multimodal agents that can process visual and textual data effectively. The project stands out for its focus on pushing the boundaries of current language models and its commitment to open research and development.

Key Features

  • Visual Instruction Tuning for enhanced multimodal capabilities
  • Support for large language models like GPT-4 and beyond
  • Community contributions and integrations with various tools and platforms
  • Regular model releases and updates, including LLaVA-NeXT and LLaVA-Plus

Use Cases

  • Researchers and developers working on advanced AI models that require visual and language understanding
  • Applications in automated customer service, where understanding visual cues is crucial
  • Educational tools that can interpret and respond to visual instructions

Advantages

  • State-of-the-art capabilities in visual instruction tuning
  • Active community and regular updates, ensuring the project stays at the forefront of AI research
  • Open-source nature allows for easy collaboration and customization

Limitations / Considerations

  • The project's cutting-edge nature may require significant computational resources for training and deployment
  • As with any AI model, there may be ethical considerations regarding data privacy and usage

Similar / Related Projects

  • DALL-E: A project focused on creating images from text descriptions, differing from LLaVA in its focus on image generation rather than multimodal understanding.
  • CLIP: A model that connects an image to the text by learning visual concepts from natural language supervision, which is more focused on image-text alignment than LLaVA's instruction tuning.
  • GPT-4: A large language model that LLaVA aims to surpass in capabilities, focusing solely on text-based AI rather than multimodal AI.

Basic Information


๐Ÿ“Š Project Information

  • Project Name: LLaVA
  • GitHub URL: https://github.com/haotian-liu/LLaVA
  • Programming Language: Python
  • โญ Stars: 23,492
  • ๐Ÿด Forks: 2,600
  • ๐Ÿ“… Created: 2023-04-17
  • ๐Ÿ”„ Last Updated: 2025-09-06

๐Ÿท๏ธ Project Topics

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๐ŸŽฎ Online Demos

๐Ÿ“š Documentation

๐ŸŽฅ Video Tutorials


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Project Information

Created on 4/17/2023
Updated on 9/8/2025