Rotary Transformer

Related tags

Deep Learning roformer
Overview

Rotary Transformer

Rotary Transformer，简称RoFormer，是我们自研的语言模型之一，主要是为Transformer结构设计了新的旋转式位置编码（Rotary Position Embedding，RoPE）。RoPE具有良好的理论性质，且是目前唯一一种可以应用到线性Attention的绝对位置编码，目前来看实验结果也颇为不错。

详细介绍：https://kexue.fm/archives/8265

依赖

bert4keras 0.10.4

参考配置：在24G显存的3090上，跑maxlen=1024，batch_size能跑到8以上。

下载

引用

Bibtex：

@techreport{zhuiyiroformer,
  title={RoFormer: Transformer with Rotary Position Embeddings - ZhuiyiAI},
  author={Jianlin Su},
  year={2021},
  url="https://github.com/ZhuiyiTechnology/roformer",
}

联系

邮箱：[email protected] 追一科技：https://zhuiyi.ai

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Comments
  • Reference to prior work

    Reference to prior work

    Hey Everybody,

    first of all congrats to the paper, it's really interesting and am looking forward to seeing its impact on the space!

    I wanted to point out that a few colleagues and me followed a similar approach to introduce translational equivariance in kernelizable attention (as is implemented in the Performer) for image classification tasks and posted it on ArXiv in the beginning of February https://arxiv.org/abs/2102.07680.

    While the approach proposed in your work is more generic, we would highly appreciate if you could also refer to our prior work in the publication.

    Best, Max

    opened by ExpectationMax 1
Owner
Zhuiyi Technology is a leading enterprise intelligent service AI company in China. We focus on deep learning and NLP.
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