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What is Llama 3.2?

The newest version of the open-source AI framework, which can be customized and utilized across different platforms, is available in several configurations: 1B, 3B, 11B, and 90B, while still offering the option to use Llama 3.1. Llama 3.2 includes a selection of large language models (LLMs) that are pretrained and fine-tuned specifically for multilingual text processing in 1B and 3B sizes, whereas the 11B and 90B models support both text and image inputs, generating text outputs. This latest release empowers users to build highly effective applications that cater to specific requirements. For applications running directly on devices, such as summarizing conversations or managing calendars, the 1B or 3B models are excellent selections. On the other hand, the 11B and 90B models are particularly suited for tasks involving images, allowing users to manipulate existing pictures or glean further insights from images in their surroundings. Ultimately, this broad spectrum of models opens the door for developers to experiment with creative applications across a wide array of fields, enhancing the potential for innovation and impact.

What is LLaVA?

LLaVA, which stands for Large Language-and-Vision Assistant, is an innovative multimodal model that integrates a vision encoder with the Vicuna language model, facilitating a deeper comprehension of visual and textual data. Through its end-to-end training approach, LLaVA demonstrates impressive conversational skills akin to other advanced multimodal models like GPT-4. Notably, LLaVA-1.5 has achieved state-of-the-art outcomes across 11 benchmarks by utilizing publicly available data and completing its training in approximately one day on a single 8-A100 node, surpassing methods reliant on extensive datasets. The development of this model included creating a multimodal instruction-following dataset, generated using a language-focused variant of GPT-4. This dataset encompasses 158,000 unique language-image instruction-following instances, which include dialogues, detailed descriptions, and complex reasoning tasks. Such a rich dataset has been instrumental in enabling LLaVA to efficiently tackle a wide array of vision and language-related tasks. Ultimately, LLaVA not only improves interactions between visual and textual elements but also establishes a new standard for multimodal artificial intelligence applications. Its innovative architecture paves the way for future advancements in the integration of different modalities.

Media

Media

Integrations Supported

ExecuTorch
AnythingLLM
Bolna
C#
CSS
DataChain
Diaflow
Elixir
Gopher
Graydient AI
Jspreadsheet
Julia
Klee
LM-Kit.NET
Microsoft Foundry Agent Service
ModelMatch
Nitric
Runpod
VESSL AI

Integrations Supported

ExecuTorch

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

www.llama.com

Company Facts

Organization Name

LLaVA

Company Website

llava-vl.github.io

Categories and Features

AI Models

Not specified

Embedding Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Open-Weight AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

AI Vision Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

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