Update README.md

README.md

@@ -28,23 +28,54 @@ How to use this model directly from the 🤗/transformers library:
 
 ```python
 from transformers import XLNetTokenizer, TFGPT2LMHeadModel
+import jieba
 
-tokenizer = XLNetTokenizer.from_pretrained('mymusise/CPM-Third-Party')
-model = TFGPT2LMHeadModel.from_pretrained("mymusise/CPM-Third-Party")
+# 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)
 
-display(text_generater('今天天气不错', max_length=20))
-display(text_generater('今天天气不错', max_length=20, do_sample=True, top_k=10, top_p=0.95))
-display(text_generater('今天天气不错', max_length=20, do_sample=True, top_k=10, top_p=0.95, repetition_penalty=2))
 
-display(text_generater('天下武功, 唯快不破', max_length=30))
-display(text_generater('天下武功, 唯快不破', max_length=30, do_sample=True, top_k=10))
+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)