The Block Transformer demonstrates comparable language modeling performance to vanilla models with equivalent parameters, achieving similar perplexity and accuracy on zero-shot evaluation tasks. It ...

The transformer architecture has emerged as the predominant framework for deep learning, playing a pivotal role in the remarkable achievements of large language models like ChatGPT. Despite its ...

Feature request I want to use BigBirdBlockSparseAttention In a decoder, But I noticed that it says in the code that it currently not works for decoders: ...

Recent Transformer-based object detectors have achieved remarkable performance on benchmark datasets, but few have addressed the real-world challenge of object detection in crowded scenes using ...

Each encoder has two layers – a self-attention layer and a feed-forward Neural Network. The decoder has both layers, but between them is an attention layer that helps it to focus on only the relevant ...

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.