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What is Smaug-72B?

Smaug-72B stands out as a powerful open-source large language model (LLM) with several noteworthy characteristics: Outstanding Performance: It leads the Hugging Face Open LLM leaderboard, surpassing models like GPT-3.5 across various assessments, showcasing its adeptness in understanding, responding to, and producing text that closely mimics human language. Open Source Accessibility: Unlike many premium LLMs, Smaug-72B is available for public use and modification, fostering collaboration and innovation within the artificial intelligence community. Focus on Reasoning and Mathematics: This model is particularly effective in tackling reasoning and mathematical tasks, a strength stemming from targeted fine-tuning techniques employed by its developers at Abacus AI. Based on Qwen-72B: Essentially, it is an enhanced iteration of the robust LLM Qwen-72B, originally released by Alibaba, which contributes to its superior performance. In conclusion, Smaug-72B represents a significant progression in the field of open-source artificial intelligence, serving as a crucial asset for both developers and researchers. Its distinctive capabilities not only elevate its prominence but also play an integral role in the continual advancement of AI technology, inspiring further exploration and development in this dynamic field.

What is Mathstral?

This year marks the 2311th anniversary of Archimedes, and in his honor, we are thrilled to unveil our first Mathstral model, a dedicated 7B architecture crafted specifically for mathematical reasoning and scientific inquiry. With a context window of 32k, this model is made available under the Apache 2.0 license. Our goal in sharing Mathstral with the scientific community is to facilitate the tackling of complex mathematical problems that require sophisticated, multi-step logical reasoning. The introduction of Mathstral aligns with our broader initiative to bolster academic efforts, developed alongside Project Numina. Much like Isaac Newton's contributions during his lifetime, Mathstral builds upon the groundwork established by Mistral 7B, with a keen focus on STEM fields. It showcases exceptional reasoning abilities within its domain, achieving impressive results across numerous industry-standard benchmarks. Specifically, it registers a score of 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, highlighting the performance enhancements in comparison to its predecessor, Mistral 7B, and underscoring the strides made in mathematical modeling. In addition to advancing individual research, this initiative seeks to inspire greater innovation and foster collaboration within the mathematical community as a whole.

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Integrations Supported

Airtrain
Diaflow
Expanse
GMTech
Hugging Face
Lunary
Ministral 3B
Mirascope
Mistral 7B
Msty
NexalAI
OpenLIT
PostgresML
Prompt Security
ReByte
Superinterface
Tune AI
Yaseen AI
bolt.diy

Integrations Supported

Airtrain
Diaflow
Expanse
GMTech
Hugging Face
Lunary
Ministral 3B
Mirascope
Mistral 7B
Msty
NexalAI
OpenLIT
PostgresML
Prompt Security
ReByte
Superinterface
Tune AI
Yaseen AI
bolt.diy

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version
Free Trial Offered?

Pricing Information

Free
Open source
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour 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

Abacus

Date Founded

2019

Company Location

United States

Company Website

huggingface.co/abacusai/Smaug-72B-v0.1

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/mathstral/

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