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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.

What is Llama?

Llama, a leading-edge foundational large language model developed by Meta AI, is designed to assist researchers in expanding the frontiers of artificial intelligence research. By offering streamlined yet powerful models like Llama, even those with limited resources can access advanced tools, thereby enhancing inclusivity in this fast-paced and ever-evolving field. The development of more compact foundational models, such as Llama, proves beneficial in the realm of large language models since they require considerably less computational power and resources, which allows for the exploration of novel approaches, validation of existing studies, and examination of potential new applications. These models harness vast amounts of unlabeled data, rendering them particularly effective for fine-tuning across diverse tasks. We are introducing Llama in various sizes, including 7B, 13B, 33B, and 65B parameters, each supported by a comprehensive model card that details our development methodology while maintaining our dedication to Responsible AI practices. By providing these resources, we seek to empower a wider array of researchers to actively participate in and drive forward the developments in the field of AI. Ultimately, our goal is to foster an environment where innovation thrives and collaboration flourishes.

Media

Media

No images available

Integrations Supported

1forAll.ai
Cake AI
Cyte
Eldil AI
Fleak
IREN Cloud
Jan
Kong AI Gateway
Llama 4 Scout
Mavvrik
Parasail
Pinecone Rerank v0
Prefactor
Scout
Sim Studio
Teneo.AI
Teradata VantageCloud
ZenML
ZeroGPT
fullmoon

API Availability

API Availability

Pricing Information

$0.1 per 1M tokens

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

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

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

www.llama.com

Categories and Features

AI Models

Not specified

Small Language Models

Not specified

Categories and Features

AI Models

Not specified

Embedding Models

Not specified

Foundation Models

Not specified

Generative AI

Not specified

Large Language Models

Not specified

Small Language Models

Not specified

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