TE
科技回声
首页24小时热榜最新最佳问答展示工作
GitHubTwitter
首页

科技回声

基于 Next.js 构建的科技新闻平台,提供全球科技新闻和讨论内容。

GitHubTwitter

首页

首页最新最佳问答展示工作

资源链接

HackerNews API原版 HackerNewsNext.js

© 2025 科技回声. 版权所有。

Making Transformer networks simpler and more efficient

2 点作者 strin超过 5 年前

1 comment

strin超过 5 年前
> In our experiments with Transformers, we observed that not all the attention heads utilize their attention span to the fullest. In fact, in a task of character-level language modeling, most of the heads were using only a small portion of their attention span. If we can take advantage of this property during training, we can reduce the computation time and memory footprint significantly