Update README.md

README.md

@@ -21,9 +21,10 @@ pipeline_tag: sentence-similarity
 
 ```python
 from transformers import BertModel, BertTokenizer
+import numpy as np
 
-model = BertModel.from_pretrained("tinydpr-acc_0.315-bs_307", cache_dir=".")
-tokenizer = BertTokenizer.from_pretrained("tinydpr-acc_0.315-bs_307", cache_dir=".")
+model = BertModel.from_pretrained("zerohell/tinydpr-acc_0.315-bs_307", cache_dir=".")
+tokenizer = BertTokenizer.from_pretrained("zerohell/tinydpr-acc_0.315-bs_307", cache_dir=".")
 
 encoded_text = tokenizer(text="采用Dureader和cmrc2018数据集进行训练。", return_tensors="pt", max_length=512,
                               padding='longest', truncation=True).to(model.device)
@@ -35,5 +36,5 @@ encoded_text = tokenizer(text="这个模型是采用什么数据集训练的？"
 encoded_text = {k: v.to(model.device) for (k, v) in encoded_text.items()}
 text_model_output2 = model(**encoded_text).pooler_output
 text_model_output2 = text_model_output2.cpu().detach().numpy()
-print(text_model_output1 @ text_model_output2)
+print(text_model_output1 @ text_model_output2.T / np.linalg.norm(text_model_output1) / np.linalg.norm(text_model_output2))
 ```