This project provides an implementation of an Encoder layers and Decoder layers of a Transformer. It includes detailed implementations of both the encoder and decoder components, utilizing multi-head ...

This model outperformed traditional encoder-decoder architectures on long sequences, allowing the team to condition on many reference documents and generate coherent and informative Wikipedia articles ...

Implementation of Transformer Encoder and Decoder. Contribute to tingyushi/transformers development by creating an account on GitHub.

This paper introduces the knowledge graph embedding and attention model based on the traditional encoder-decoder model. The KG embedded layer improve entities pair accuracy in diffident languages, by ...

This article emphasizes such a fact that skip connections between encoder and decoder are not equally effective, attempts to adaptively allocate the aggregation weights that represent differentiated ...

The Transformer architecture implements an encoder-decoder structure without recurrence and convolutions. Taking cognizance of the importance of Transformers in machine learning and AI, we have listed ...

This comprehensive guide delves into decoder-based Large Language Models (LLMs), exploring their architecture, innovations, and applications in natural language processing. Highlighting the evolution ...