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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 Llama 2?
We are excited to unveil the latest version of our open-source large language model, which includes model weights and initial code for the pretrained and fine-tuned Llama language models, ranging from 7 billion to 70 billion parameters. The Llama 2 pretrained models have been crafted using a remarkable 2 trillion tokens and boast double the context length compared to the first iteration, Llama 1. Additionally, the fine-tuned models have been refined through the insights gained from over 1 million human annotations. Llama 2 showcases outstanding performance compared to various other open-source language models across a wide array of external benchmarks, particularly excelling in reasoning, coding abilities, proficiency, and knowledge assessments. For its training, Llama 2 leveraged publicly available online data sources, while the fine-tuned variant, Llama-2-chat, integrates publicly accessible instruction datasets alongside the extensive human annotations mentioned earlier. Our project is backed by a robust coalition of global stakeholders who are passionate about our open approach to AI, including companies that have offered valuable early feedback and are eager to collaborate with us on Llama 2. The enthusiasm surrounding Llama 2 not only highlights its advancements but also marks a significant transformation in the collaborative development and application of AI technologies. This collective effort underscores the potential for innovation that can emerge when the community comes together to share resources and insights.
Integrations Supported
AI/ML API
Agenta
AiAssistWorks
Azure Marketplace
Batteries Included
Code Llama
Deasie
Decopy AI
Diaflow
Entry Point AI
Integrations Supported
AI/ML API
Agenta
AiAssistWorks
Azure Marketplace
Batteries Included
Code Llama
Deasie
Decopy AI
Diaflow
Entry Point AI
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
Windows
Mac
On-Prem
Linux
Customer Service / Support
Not specified
Customer Service / Support
Not specified
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
Meta
Date Founded
2004
Company Location
United States
Company Website
www.llama.com
Company Facts
Organization Name
Meta
Date Founded
2004
Company Location
United States
Company Website
ai.meta.com/llama/
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
Retrieval-Augmented Generation (RAG)
Not specified
Small Language Models
Not specified
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
Large Language Models
Not specified
Open-Weight AI Models
Not specified
Small Language Models
Not specified