PyTorch provides a set of abstractions and features that can help build more complex models, with support for tensors and neural networks. Tensors make it easy to work with large multidimensional ...

The ability to work with tensors is fundamental in order to build models that can analyze and make decisions on large datasets. Two of the most popular tools for this purpose are PyTorch which was ...

A startup called TensorStax says it’s looking to bring artificial intelligence-powered automation to the unyielding world of data engineering after raising $5 million in seed funding. Today’s ...

Tensors play a pivotal role in AI and deep learning systems, and share a common heritage with both physics and advanced mathematics. All of which makes it extremely difficult to lock down a ...

In a notable step toward democratizing vision-language model development, Hugging Face has released nanoVLM, a compact and educational PyTorch-based framework that allows researchers and developers to ...

Impact Statement: Autoencoder is a popular data-driven modeling technology in deep learning. It can deal with the nonlinear relationships among process variables, and has a powerful feature extraction ...

This library provides the capability to emulate MX-compatble formats and bfloat quantization in pytorch, enabling data science exploration ... torch.bmm) between two MX tensors Elementwise ops (GELU, ...