Update README.md

README.md

@@ -137,7 +137,7 @@ In short:
 3. 🟡 shibing624/text2vec-base-chinese (ov-qint8), int8 quantization with OV incurs a small performance hit on some tasks, and a tiny performance gain on others, when quantizing with [Chinese STSB](https://huggingface.co/datasets/PhilipMay/stsb_multi_mt). Additionally, it results in a [4.78x speedup](https://sbert.net/docs/sentence_transformer/usage/efficiency.html#benchmarks) on CPU.
 
 - usage: shibing624/text2vec-base-chinese (onnx-O4), for gpu
-```
+```python
 from sentence_transformers import SentenceTransformer
 
 model = SentenceTransformer(
@@ -145,16 +145,17 @@ model = SentenceTransformer(
     backend="onnx",
     model_kwargs={"file_name": "model_O4.onnx"},
 )
-embeddings = model.encode(["怎么开通银行卡", "如何更换花呗绑定银行卡", "花呗更改绑定银行卡"])
+embeddings = model.encode(["如何更换花呗绑定银行卡", "花呗更改绑定银行卡", "你是谁"])
 print(embeddings.shape)
-
 similarities = model.similarity(embeddings, embeddings)
 print(similarities)
 ```
 
 
 - usage: shibing624/text2vec-base-chinese (ov), for cpu
-```
+```python
+# pip install 'optimum[openvino]'
+
 from sentence_transformers import SentenceTransformer
 
 model = SentenceTransformer(
@@ -162,15 +163,15 @@ model = SentenceTransformer(
     backend="openvino",
 )
 
-embeddings = model.encode(["怎么开通银行卡", "如何更换花呗绑定银行卡", "花呗更改绑定银行卡"])
+embeddings = model.encode(["如何更换花呗绑定银行卡", "花呗更改绑定银行卡", "你是谁"])
 print(embeddings.shape)
-
 similarities = model.similarity(embeddings, embeddings)
 print(similarities)
 ```
 
 - usage: shibing624/text2vec-base-chinese (ov-qint8), for cpu
-```
+```python
+# pip install optimum
 from sentence_transformers import SentenceTransformer
 
 model = SentenceTransformer(
@@ -178,9 +179,8 @@ model = SentenceTransformer(
     backend="onnx",
     model_kwargs={"file_name": "model_qint8_avx512_vnni.onnx"},
 )
-embeddings = model.encode(["怎么开通银行卡", "如何更换花呗绑定银行卡", "花呗更改绑定银行卡"])
+embeddings = model.encode(["如何更换花呗绑定银行卡", "花呗更改绑定银行卡", "你是谁"])
 print(embeddings.shape)
-
 similarities = model.similarity(embeddings, embeddings)
 print(similarities)
 ```