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What is TinyLlama?

The TinyLlama project aims to pretrain a Llama model featuring 1.1 billion parameters, leveraging a vast dataset of 3 trillion tokens. With effective optimizations, this challenging endeavor can be accomplished in only 90 days, making use of 16 A100-40G GPUs for processing power. By preserving the same architecture and tokenizer as Llama 2, we ensure that TinyLlama remains compatible with a range of open-source projects built upon Llama. Moreover, the model's streamlined architecture, with its 1.1 billion parameters, renders it ideal for various applications that demand minimal computational power and memory. This adaptability allows developers to effortlessly incorporate TinyLlama into their current systems and processes, fostering innovation in resource-constrained environments. As a result, TinyLlama not only enhances accessibility but also encourages experimentation in the field of machine learning.

What is Llama 4 Scout?

Llama 4 Scout represents a leap forward in multimodal AI, featuring 17 billion active parameters and a groundbreaking 10 million token context length. With its ability to integrate both text and image data, Llama 4 Scout excels at tasks like multi-document summarization, complex reasoning, and image grounding. It delivers superior performance across various benchmarks and is particularly effective in applications requiring both language and visual comprehension. Scout's efficiency and advanced capabilities make it an ideal solution for developers and businesses looking for a versatile and powerful model to enhance their AI-driven projects.

Media

No images available

Media

Integrations Supported

AiAssistWorks
BLACKBOX AI
Baseten
C#
CentML
F#
Go
Java
LLM Council
Llama
Llama 4 Maverick
R
Ruby
Rust
SQL
Scala
Snowflake
Snowflake Cortex AI
TypeScript
kluster.ai

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

Windows
Mac
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

TinyLlama

Company Website

github.com/jzhang38/TinyLlama

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

ai.meta.com

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Small Language Models

Not specified

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