README.md

metadata

language: zh
tags:
  - roformer
inference: false

介绍

tf版本

https://github.com/ZhuiyiTechnology/roformer

pytorch版本

https://github.com/JunnYu/RoFormer_pytorch

使用

git clone https://github.com/JunnYu/RoFormer_pytorch
cd RoFormer_pytorch
import torch
from model import RoFormerModel, RoFormerTokenizer
tokenizer = RoFormerTokenizer.from_pretrained("junnyu/roformer_chinese_base")
model = RoFormerModel.from_pretrained("junnyu/roformer_chinese_base")
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs).last_hidden_state
print(outputs.shape)

引用

Bibtex：

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