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Lecture 12.1 Self-attention
DLVU
30 พ.ย. 2020
การดู 69,105 ครั้ง
Attention is all you need (Transformer) - Model explanation (including math), Inference and Training
Lecture 12.2 Transformers
MIT 6.S191 (2023): Recurrent Neural Networks, Transformers, and Attention
Lecture 12.3 Famous transformers (BERT, GPT-2, GPT-3)
The math behind Attention: Keys, Queries, and Values matrices
Attention for RNN Seq2Seq Models (1.25x speed recommended)
Coding a Transformer from scratch on PyTorch, with full explanation, training and inference.
What are Transformer Models and how do they work?
Stanford CS25: V2 I Introduction to Transformers w/ Andrej Karpathy
A Dive Into Multihead Attention, Self-Attention and Cross-Attention
CS480/680 Lecture 19: Attention and Transformer Networks
Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!!
MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention
LSTM is dead. Long Live Transformers!
Attention Is All You Need
Attention Is All You Need - Paper Explained
Rasa Algorithm Whiteboard - Transformers & Attention 1: Self Attention
Pytorch Transformers from Scratch (Attention is all you need)
Attention for Neural Networks, Clearly Explained!!!
Self Attention in Transformer Neural Networks (with Code!)