<h1 align="center"> CPM </h1>

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

The One Thing You Need to Know is this model is not uploaded by official, the conver script is here

Overview

How to use

How to use this model directly from the 🤗/transformers library:

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-FP16')
model = TFGPT2LMHeadModel.from_pretrained("mymusise/CPM-GPT2-FP16")

How to generate text

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

You can try it on colab

<a href="https://colab.research.google.com/github/mymusise/CPM-TF2Transformer/blob/main/demo-fp16.ipynb"> <img alt="Build" src="https://colab.research.google.com/assets/colab-badge.svg"> </a>