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What is Syn?

Syn is an advanced Japanese large language model, developed through a collaboration between Upstage and Karakuri, featuring nearly 14 billion parameters and specifically designed for enterprise use in various fields such as finance, manufacturing, legal, and healthcare. It excels in benchmark evaluations on the Weights & Biases Nejumi Leaderboard, demonstrating top-tier performance in accuracy and alignment while maintaining cost-effectiveness through its efficient architecture, which draws inspiration from Solar Mini. Furthermore, Syn showcases outstanding capabilities in Japanese "truthfulness" and safety, skillfully understanding intricate expressions and specialized jargon relevant to different industries. Its flexible fine-tuning options allow for the seamless integration of proprietary data and domain knowledge. Built for widespread deployment, Syn is versatile enough to operate in on-premises environments, AWS Marketplace, and cloud infrastructures, reinforced by strong security and compliance protocols tailored to meet enterprise demands. Impressively, by leveraging AWS Trainium, Syn can reduce training costs by approximately 50 percent compared to traditional GPU setups, enabling rapid customization for a variety of applications. This cutting-edge model not only boosts operational efficiency but also opens doors to more agile and responsive solutions for enterprises, ultimately transforming how businesses approach their challenges. Enhancing productivity and innovation, Syn positions itself as a vital tool for organizations looking to thrive in an increasingly competitive landscape.

What is Solar Mini?

Solar Mini is a cutting-edge pre-trained large language model that rivals the capabilities of GPT-3.5 and delivers answers 2.5 times more swiftly, all while keeping its parameter count below 30 billion. In December 2023, it achieved the highest rank on the Hugging Face Open LLM Leaderboard by employing a 32-layer Llama 2 architecture initialized with high-quality Mistral 7B weights, along with a groundbreaking technique called "depth up-scaling" (DUS) that efficiently increases the model's depth without requiring complex modules. After the DUS approach is applied, the model goes through additional pretraining to enhance its performance, and it incorporates instruction tuning designed in a question-and-answer style specifically for Korean, which refines its ability to respond to user queries effectively. Moreover, alignment tuning is implemented to ensure that its outputs are in harmony with human or advanced AI expectations. Solar Mini consistently outperforms competitors such as Llama 2, Mistral 7B, Ko-Alpaca, and KULLM across various benchmarks, proving that innovative architectural approaches can lead to remarkably efficient and powerful AI models. This achievement not only highlights the effectiveness of Solar Mini but also emphasizes the importance of continually evolving strategies in the AI field.

Media

Media

Integrations Supported

Upstage AI
AWS Marketplace
AWS Trainium
Amazon Web Services (AWS)
Solar Mini

Integrations Supported

Upstage AI
Hugging Face
Llama 2
Mistral 7B
Syn

API Availability

API Availability

Pricing Information

$0.1 per 1M tokens

Pricing Information

$0.1 per 1M tokens

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Upstage AI

Date Founded

2020

Company Location

United States

Company Website

www.upstage.ai/news/introducing-upstage-japan

Company Facts

Organization Name

Upstage AI

Date Founded

2020

Company Location

United States

Company Website

www.upstage.ai/blog/en/introducing-solar-mini-compact-yet-powerful

Categories and Features

AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Small Language Models

Not specified

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