---
language: zh
widget:
- text: "今天是下雨天"
- text: "走向森林"
---
CPM
CPM(Chinese Pre-Trained Language Models), which has 2.6B parameters, made by the research team of Beijing Zhiyuan Institute of artificial intelligence and Tsinghua University @TsinghuaAI.
[repo: CPM-Generate](https://github.com/TsinghuaAI/CPM-Generate)
The One Thing You Need to Know is this model is not uploaded by official, the conver script is [here](https://github.com/mymusise/CPM-TF2Transformer/blob/main/transfor_CMP.ipynb)
# Overview
- **Language model**: CPM
- **Model size**: 2.6B parameters
- **Language**: Chinese
# How to use
How to use this model directly from the 🤗/transformers library:
```python
from transformers import XLNetTokenizer, TFGPT2LMHeadModel
import jieba
# add spicel process
class XLNetTokenizer(XLNetTokenizer):
translator = str.maketrans(" \n", "\u2582\u2583")
def _tokenize(self, text, *args, **kwargs):
text = [x.translate(self.translator) for x in jieba.cut(text, cut_all=False)]
text = " ".join(text)
return super()._tokenize(text, *args, **kwargs)
def _decode(self, *args, **kwargs):
text = super()._decode(*args, **kwargs)
text = text.replace(' ', '').replace('\u2582', ' ').replace('\u2583', '\n')
return text
tokenizer = XLNetTokenizer.from_pretrained('mymusise/CPM-GPT2')
model = TFGPT2LMHeadModel.from_pretrained("mymusise/CPM-GPT2")
```
How to generate text
```python
from transformers import TextGenerationPipeline
text_generater = TextGenerationPipeline(model, tokenizer)
texts = [
'今天天气不错',
'天下武功, 唯快不',
"""
我们在火星上发现了大量的神奇物种。有神奇的海星兽,身上是粉色的,有5条腿;有胆小的猫猫兽,橘色,有4条腿;有令人恐惧的蜈蚣兽,全身漆黑,36条腿;有纯洁的天使兽,全身洁白无瑕,有3条腿;有贪吃的汪汪兽,银色的毛发,有5条腿;有蛋蛋兽,紫色,8条腿。
请根据上文,列出一个表格,包含物种名、颜色、腿数量。
|物种名|颜色|腿数量|
|亚古兽|金黄|2|
|海星兽|粉色|5|
|猫猫兽|橘色|4|
|蜈蚣兽|漆黑|36|
"""
]
for text in texts:
token_len = len(tokenizer._tokenize(text))
print(text_generater(text, max_length=token_len + 15, top_k=1, use_cache=True, prefix='')[0]['generated_text'])
print(text_generater(text, max_length=token_len + 15, do_sample=True, top_k=5)[0]['generated_text'])
```
![avatar](https://github.com/mymusise/CPM-TF2Transformer/raw/main/example-cpm.png)