---
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
```python
git clone https://github.com/JunnYu/RoFormer_pytorch
cd RoFormer_pytorch
import torch
from model import RoFormerForMaskedLM, RoFormerTokenizer

text = "今天[MASK]很好，我[MASK]去公园玩。"
tokenizer = RoFormerTokenizer.from_pretrained("junnyu/roformer_chinese_base")
model = RoFormerForMaskedLM.from_pretrained("junnyu/roformer_chinese_base")
inputs = tokenizer(text, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs).logits[0]
outputs_sentence = ""
for i, id in enumerate(tokenizer.encode(text)):
    if id == tokenizer.mask_token_id:
        tokens = tokenizer.convert_ids_to_tokens(outputs[i].topk(k=5)[1])
        outputs_sentence += "[" + "||".join(tokens) + "]"
    else:
        outputs_sentence += "".join(
            tokenizer.convert_ids_to_tokens([id], skip_special_tokens=True))
print(outputs_sentence)
# 今天[天气||天||心情||阳光||空气]很好，我[想||要||打算||准备||喜欢]去公园玩。
```
## 引用

Bibtex：

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