In recent years, with the rapid development of large model technology, the Transformer architecture has gained widespread attention as its core cornerstone. This article will delve into the principles ...

Seq2Seq is essentially an abstract deion of a class of problems, rather than a specific model architecture, just as the ...

Discover the key differences between Moshi and Whisper speech-to-text models. Speed, accuracy, and use cases explained for your next project.

This repository contains the first collection of paired encoder-only and decoder-only models trained with identical data, architecture, and training recipes. Ettin enables fair comparisons between ...

NVIDIA's TensorRT-LLM now supports encoder-decoder models with in-flight batching, offering optimized inference for AI applications. Discover the enhancements for generative AI on NVIDIA GPUs.

An Encoder-decoder architecture in machine learning efficiently translates one sequence data form to another.

The encoder processes the input and passes a contextual representation to the decoder, which then generates the output. This structure is especially suited for tasks like machine translation, ...

Depth estimation from a single image is a fundamental problem in the field of computer vision. With the great success of deep learning techniques, various self-supervised monocular depth estimation ...