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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 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.

Media

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Media

Integrations Supported

Runpod

Integrations Supported

Runpod
AI4Chat
Aili
Alpaca
Automi
Cyte
Evertune
Fleak
Genaios
InfoBaseAI
Kiin
Klee
NVIDIA Brev
Ollama
Prompt Security
RankGPT
Solar Mini
Unsloth
Waveloom
ZenML

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
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/llama/

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

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