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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.

What is LFM2?

LFM2 is a cutting-edge series of on-device foundation models specifically engineered to deliver an exceptionally fast generative-AI experience across a wide range of devices. It employs an innovative hybrid architecture that enables decoding and pre-filling speeds up to twice as fast as competing models, while also improving training efficiency by as much as threefold compared to earlier versions. Striking a perfect balance between quality, latency, and memory use, these models are ideally suited for embedded system applications, allowing for real-time, on-device AI capabilities in smartphones, laptops, vehicles, wearables, and many other platforms. This results in millisecond-level inference, enhanced device longevity, and complete data sovereignty for users. Available in three configurations with 0.35 billion, 0.7 billion, and 1.2 billion parameters, LFM2 demonstrates superior benchmark results compared to similarly sized models, excelling in knowledge recall, mathematical problem-solving, adherence to multilingual instructions, and conversational dialogue evaluations. With such impressive capabilities, LFM2 not only elevates the user experience but also establishes a new benchmark for on-device AI performance, paving the way for future advancements in the field.

Media

Media

Integrations Supported

1min.AI
AICamp
AnythingLLM
Automi
Batteries Included
Browser Use
Ema
Featherless
GaiaNet
Gopher
HelpNow Agentic AI Platform
Jspreadsheet
LM Studio
Lakera
Microsoft Foundry Agent Service
NVIDIA Brev
Odyssey
Second State
TESS AI
Waveloom

API Availability

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Standard 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

ai.meta.com/llama/

Company Facts

Organization Name

Liquid AI

Date Founded

2023

Company Location

United States

Company Website

www.liquid.ai/blog/liquid-foundation-models-v2-our-second-series-of-generative-ai-models

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

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

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