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Description
Apache Yetus comprises a suite of libraries and tools designed to facilitate the contribution and release workflows for software projects. It offers a comprehensive framework for automatically validating new contributions against a range of standards recognized by the community, alongside features for documenting a clearly defined supported interface for downstream projects. Additionally, it equips release managers with tools to create release documentation based on data sourced from community issue trackers and source code repositories. Predominantly, the software is developed using shell and various scripting languages, with the project's name derived from a term linked to the Cymbium genus of gastropods, paying homage to shell code. The Yetus Precommit build, patch, and continuous integration suite empowers projects to formalize their criteria for patch acceptance and assess incoming contributions before they reach the review stage by a committer. Furthermore, the Audience Annotations feature enables developers to utilize Java Annotations to indicate which segments of their Java library are intended for public consumption, enhancing clarity for users. This combination of tools and features makes Yetus an invaluable resource for software development communities looking to streamline their processes.
Description
In honor of Archimedes, whose 2311th anniversary we celebrate this year, we are excited to introduce our inaugural Mathstral model, a specialized 7B architecture tailored for mathematical reasoning and scientific exploration. This model features a 32k context window and is released under the Apache 2.0 license. Our intention behind contributing Mathstral to the scientific community is to enhance the pursuit of solving advanced mathematical challenges that necessitate intricate, multi-step logical reasoning. The launch of Mathstral is part of our wider initiative to support academic endeavors, developed in conjunction with Project Numina. Much like Isaac Newton during his era, Mathstral builds upon the foundation laid by Mistral 7B, focusing on STEM disciplines. It demonstrates top-tier reasoning capabilities within its category, achieving remarkable results on various industry-standard benchmarks. Notably, it scores 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, showcasing the performance differences by subject between Mathstral 7B and its predecessor, Mistral 7B, further emphasizing the advancements made in mathematical modeling. This initiative aims to foster innovation and collaboration within the mathematical community.
API Access
Has API
API Access
Has API
Integrations
1min.AI
Arize Phoenix
Codestral Mamba
DataChain
Expanse
Hugging Face
MindMac
Mistral Large
Mixtral 8x7B
NexalAI
Integrations
1min.AI
Arize Phoenix
Codestral Mamba
DataChain
Expanse
Hugging Face
MindMac
Mistral Large
Mixtral 8x7B
NexalAI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Apache Software Foundation
Founded
1999
Country
United States
Website
yetus.apache.org
Vendor Details
Company Name
Mistral AI
Founded
2023
Country
France
Website
mistral.ai/news/mathstral/
Product Features
Software Testing
Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing
