Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

For example, you might use a multi-task learning approach, where you train your encoder-decoder model on multiple related tasks simultaneously, and share some parameters across them. This can ...

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. The IRS ...

Interact with a trained chatbot that uses sequence to sequence model with luong attention mechanism over jointly trained encoder-decoder modules and implementation of greedy search decoding module.

In this article, we are going to see how we can remove noise from the image data using an encoder-decoder model. Having clear and processed images or videos is very important in any computer vision ...

Abstract: This research paper introduces an innovative AI coaching approach by integrating vision-encoder-decoder models. The feasibility of this method is demonstrated using a Vision Transformer as ...

Models like BERT and T5 are trained with an encoder only or encoder-decoder architectures. These models have demonstrated near-universal state of the art performance across thousands of natural ...

GPT-like transformer model consisting of an encoder and a decoder for various natural language processing tasks, including text classification and language modeling.