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What is Hydrogen-1.0?

Hydrogen-1.0 is an innovative scientific language model featuring open weights, developed by Deep Principle through the post-training of GLM-5.3, utilizing a wide variety of data sources such as chemistry, materials science, life sciences, laboratory notes, and research methodologies. The primary goal of this model is to aid researchers in addressing scientific questions, clarifying derivations, analyzing reaction pathways, interpreting spectra, designing experiments, and formulating hypotheses regarding materials. Its capabilities encompass scientific computing workflows, exploration of reaction networks, NMR structure analysis, experiment planning, and material discovery. Users can easily obtain the model by downloading its weights from platforms like Hugging Face and ModelScope, accessing it via API through NeuroSpark, or utilizing Deep Principle's Mira AI Scientist. Additionally, Hydrogen-1.0 can be run locally with proper hardware and software setups. It is crucial for researchers to critically evaluate the model's outputs in context with relevant evidence and scientific constraints, promoting responsible usage in their research endeavors. Consequently, Hydrogen-1.0 signifies a major leap forward in enhancing the efficiency and accessibility of scientific research, ultimately fostering innovation and collaboration in various fields. This advancement opens new avenues for interdisciplinary studies, bridging gaps between different scientific domains.

What is EXAONE Deep?

EXAONE Deep is a suite of sophisticated language models developed by LG AI Research, featuring configurations of 2.4 billion, 7.8 billion, and 32 billion parameters. These models are particularly adept at tackling a range of reasoning tasks, excelling in domains like mathematics and programming evaluations. Notably, the 2.4B variant stands out among its peers of comparable size, while the 7.8B model surpasses both open-weight counterparts and the proprietary model OpenAI o1-mini. Additionally, the 32B variant competes strongly with leading open-weight models in the industry. The accompanying repository not only provides comprehensive documentation, including performance metrics and quick-start guides for utilizing EXAONE Deep models with the Transformers library, but also offers in-depth explanations of quantized EXAONE Deep weights structured in AWQ and GGUF formats. Users will also find instructions on how to operate these models locally using tools like llama.cpp and Ollama, thereby broadening their understanding of the EXAONE Deep models' potential and ensuring easier access to their powerful capabilities. This resource aims to empower users by facilitating a deeper engagement with the advanced functionalities of the models.

Media

No images available

Media

Integrations Supported

Hugging Face
ModelScope

Integrations Supported

Ollama
OpenAI
OpenAI o1-mini

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Deep Principle

Date Founded

2024

Company Location

China

Company Website

blog.deepprinciple.com/introducing-hydrogen-1.0/

Company Facts

Organization Name

LG

Date Founded

1947

Company Location

South Korea

Company Website

github.com/LG-AI-EXAONE/EXAONE-Deep

Categories and Features

AI Models

Not specified

AI Science

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Open-Weight AI Models

Not specified

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