This repository contains an implementation of the Transformer Encoder-Decoder model from scratch in C++. The objective is to build a sequence-to-sequence model that leverages pre-trained word ...

I've been following this to implement a bert2bert seq2seq model which works pretty well. Now I would like to change this to mbart (facebook/mbart-large-50) instead of bert. I'm very new to this, but ...

But not all transformer applications require both the encoder and decoder module. For example, the GPT family of large language models uses stacks of decoder modules to generate text.

Decoder-only models. In the last few years, large neural networks have achieved impressive results across a wide range of tasks. Models like BERT and T5 are trained with an encoder only or ...

Microsoft today detailed Mu, its latest small language model (SML) for Copilot+ PCs, which maps NL queries to Settings ...

The transformer model has become a state-of-the-art model in Natural Language Processing. The initial transformer model, known as the vanilla transformer model, is designed to improve some prominent ...

Tamil language processing in NLP has yet to be outstanding, mainly because of the absence of high-quality resources. In this project, a novel approach to address these limitations is to build an ...