filmov
tv
Attention Is All You Need
Показать описание
Abstract:
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely. Experiments on two machine translation tasks show these models to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 28.4 BLEU on the WMT 2014 English-to-German translation task, improving over the existing best results, including ensembles by over 2 BLEU. On the WMT 2014 English-to-French translation task, our model establishes a new single-model state-of-the-art BLEU score of 41.0 after training for 3.5 days on eight GPUs, a small fraction of the training costs of the best models from the literature. We show that the Transformer generalizes well to other tasks by applying it successfully to English constituency parsing both with large and limited training data.
Authors:
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin
0:27:07
Attention Is All You Need
0:05:34
Attention mechanism: Overview
0:13:05
Transformer Neural Networks - EXPLAINED! (Attention is all you need)
0:58:04
Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
0:15:01
Illustrated Guide to Transformers Neural Network: A step by step explanation
0:26:10
Attention in transformers, visually explained | Chapter 6, Deep Learning
0:36:44
Attention Is All You Need - Paper Explained
0:13:56
Attention is all you need explained
0:15:51
Attention for Neural Networks, Clearly Explained!!!
0:09:11
Transformers, explained: Understand the model behind GPT, BERT, and T5
0:08:38
Transformers: The best idea in AI | Andrej Karpathy and Lex Fridman
0:27:14
But what is a GPT? Visual intro to transformers | Chapter 5, Deep Learning
1:19:24
Live -Transformers Indepth Architecture Understanding- Attention Is All You Need
0:36:15
Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!!
0:05:50
What are Transformers (Machine Learning Model)?
0:10:08
The Transformer neural network architecture EXPLAINED. “Attention is all you need”
0:20:39
AI Language Models & Transformers - Computerphile
0:04:30
Attention Mechanism In a nutshell
0:57:10
Pytorch Transformers from Scratch (Attention is all you need)
0:36:16
The math behind Attention: Keys, Queries, and Values matrices
0:19:59
Transformers for beginners | What are they and how do they work
1:22:38
CS480/680 Lecture 19: Attention and Transformer Networks
0:13:42
Transformer (Attention is all you need)
0:20:12
How do transformers work? (Attention is all you need)
Комментарии