Vector Post-Training Quantization (VPTQ) is a novel Post-Training Quantization method that leverages Vector Quantization to high accuracy on LLMs at an extremely low bit-width (<2-bit). VPTQ can ...
A Discrete Function (DF) Method for Highly Efficient Magnetization Vector Inversion of Magnetic Data
Abstract: The three-direction magnetization intensities of a source can be obtained by the magnetization vector inversion (MVI) of magnetic data, and therefore, MVI can be well applied to a magnetic ...
Koheesio is a versatile framework that supports multiple implementations and works seamlessly with various data processing libraries or frameworks. This ensures that Koheesio can handle any data ...
Amazon.com said it will invest $50 billion to expand artificial intelligence and high-performance computing capabilities for its cloud business’ U.S. government customers. The investment will add ...
Abstract: This paper introduces DSrepair, a knowledge-enhanced program repair approach designed to repair the buggy code generated by LLMs in the data science domain. DSrepair uses knowledge graph ...
As the rapid rise of artificial intelligence transforms industries, it’s straining the energy-hungry data centers that power it. These facilities, essential to running complex AI models and digital ...
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