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Description

The overwhelming amount of information available poses a significant challenge to advancements in science. With the rapid expansion of scientific literature and data, pinpointing valuable insights within this vast sea of information has become increasingly difficult. Nowadays, people rely on search engines to access scientific knowledge, yet these tools alone cannot effectively categorize and organize this complex information. Galactica is an advanced language model designed to capture, synthesize, and analyze scientific knowledge. It is trained on a diverse array of scientific materials, including research papers, reference texts, knowledge databases, and other relevant resources. In various scientific tasks, Galactica demonstrates superior performance compared to existing models. For instance, on technical knowledge assessments involving LaTeX equations, Galactica achieves a score of 68.2%, significantly higher than the 49.0% of the latest GPT-3 model. Furthermore, Galactica excels in reasoning tasks, outperforming Chinchilla in mathematical MMLU with scores of 41.3% to 35.7%, and surpassing PaLM 540B in MATH with a notable 20.4% compared to 8.8%. This indicates that Galactica not only enhances accessibility to scientific information but also improves our ability to reason through complex scientific queries.

Description

The NVIDIA Llama Nemotron family comprises a series of sophisticated language models that are fine-tuned for complex reasoning and a wide array of agentic AI applications. These models shine in areas such as advanced scientific reasoning, complex mathematics, coding, following instructions, and executing tool calls. They are designed for versatility, making them suitable for deployment on various platforms, including data centers and personal computers, and feature the ability to switch reasoning capabilities on or off, which helps to lower inference costs during less demanding tasks. The Llama Nemotron series consists of models specifically designed to meet different deployment requirements. Leveraging the foundation of Llama models and enhanced through NVIDIA's post-training techniques, these models boast a notable accuracy improvement of up to 20% compared to their base counterparts while also achieving inference speeds that can be up to five times faster than other leading open reasoning models. This remarkable efficiency allows for the management of more intricate reasoning challenges, boosts decision-making processes, and significantly lowers operational expenses for businesses. Consequently, the Llama Nemotron models represent a significant advancement in the field of AI, particularly for organizations seeking to integrate cutting-edge reasoning capabilities into their systems.

API Access

Has API

API Access

Has API

Screenshots View All

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Screenshots View All

Integrations

BLACKBOX AI
Llama
NVIDIA AI Data Platform
NVIDIA AI Enterprise
NVIDIA Blueprints
NVIDIA DGX Cloud
NVIDIA NIM
NVIDIA NeMo
Nebius Token Factory

Integrations

BLACKBOX AI
Llama
NVIDIA AI Data Platform
NVIDIA AI Enterprise
NVIDIA Blueprints
NVIDIA DGX Cloud
NVIDIA NIM
NVIDIA NeMo
Nebius Token Factory

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

meta.com

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

www.nvidia.com/en-us/ai-data-science/foundation-models/llama-nemotron/

Product Features

Product Features

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