BART is an encoder-decoder model that is particularly effective for sequence-to-sequence tasks like summarization, translation, and text generation. Florence-2 is a vision-language model from ...

并行draft的速度优势已经很明显，下一步要补上的，是block内部的因果一致性。

来讲讲 Transformer 架构的基本原理？Encoder 和 Decoder 是什么？Transformer 这道题想听的不是「Attention is all you need」这种口号，而是 RNN 卡在哪两点、Attention 怎么把这两点都破了、三种架构变体打了一圈为什么是 Decoder-only 赢到现在。 👔面试官：来讲讲 Transformer 架构 ...

A complete walkthrough of implementing the original Attention Is All You Need encoder-decoder Transformer—no torch. nn.Transformer, no shortcuts. The 2017 paper "Attention Is All You Need" by Vaswani ...

This post tries to explain inner blocks of Transformer architecture which is the secret sauce behind all the Large language models and Chatbots with an example. Historically RNN’s like LSTM’s and ...

CNNs are specialized deep neural networks for processing data with a grid-like topology, such as images. A CNN automatically detects the important features without any human supervision. They are ...

Abstract: Multiscale video transformers have been explored in a wide variety of vision tasks. To date, however, the multiscale processing has been confined to the encoder or decoder alone. We present ...