Jun 17, 2023 · Delve into Transformer architectures: from the original encoder-decoder structure, to BERT & RoBERTa encoder-only models, to the GPT series focused on decoding. Explore their evolution, strengths, & applications in NLP tasks.

Transformer-based encoder-decoder models are the result of years of research on representation learning and model architectures. This notebook provides a short summary of the history of neural encoder-decoder models.

Apr 29, 2023 · One of the most popular transformer encoder-decoder models is the T5 (Text-to-Text Transfer Transformer), which was introduced by Google in 2019. The T5 can be fine-tuned for a wide range of...

Mar 17, 2023 · Transformer was an encoder-decoder neural network with a core component — self-attention mechanism.

Encoder models use only the encoder of a Transformer model. At each stage, the attention layers can access all the words in the initial sentence. These models are often characterized as having “bi-directional” attention, and are often called auto-encoding models.

Apr 27, 2024 · In this comprehensive guide, we will explore the inner workings of decoder-based LLMs, delving into the fundamental building blocks, architectural innovations, and implementation details that have propelled these models to the forefront of NLP research and applications.

Apr 8, 2023 · Traditionally, most of the seq2seq task is resolved by the Encoder-Decoder framework which requires an encoder to encode the source sequence and a decoder to generate the target text. Recently, a bunch of new approaches have emerged that apply decoder-only language models directly to the seq2seq task.

EncoderDecoderModel can be randomly initialized from an encoder and a decoder config. In the following example, we show how to do this using the default BertModel configuration for the encoder and the default BertForCausalLM configuration for the decoder. Initialising EncoderDecoderModel from a pretrained encoder and a pretrained decoder.

Transformer-based encoder-decoder models are the result of years of research on representation learning and model architectures. This notebook provides a short summary of the history of...

Dec 17, 2024 · Depending on the specific task, the Transformer architecture can be divided into three main types: encoder-only, decoder-only, and encoder-decoder models. Each variant serves a distinct...