Chess Grandmaster-Level Chess Without Search Paper • 2402.04494 • Published Feb 7, 2024 • 69 The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits Paper • 2402.17764 • Published Feb 27, 2024 • 627
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits Paper • 2402.17764 • Published Feb 27, 2024 • 627
Reading list A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay Paper • 1803.09820 • Published Mar 26, 2018 • 1 SGDR: Stochastic Gradient Descent with Warm Restarts Paper • 1608.03983 • Published Aug 13, 2016 • 1
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay Paper • 1803.09820 • Published Mar 26, 2018 • 1
Chess Grandmaster-Level Chess Without Search Paper • 2402.04494 • Published Feb 7, 2024 • 69 The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits Paper • 2402.17764 • Published Feb 27, 2024 • 627
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits Paper • 2402.17764 • Published Feb 27, 2024 • 627
Reading list A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay Paper • 1803.09820 • Published Mar 26, 2018 • 1 SGDR: Stochastic Gradient Descent with Warm Restarts Paper • 1608.03983 • Published Aug 13, 2016 • 1
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay Paper • 1803.09820 • Published Mar 26, 2018 • 1
