Update README.md

README.md

@@ -27,12 +27,4 @@ model = ORTModelForCustomTasks.from_pretrained("vamsibanda/sbert-all-MiniLM-L12-
 tokenizer = AutoTokenizer.from_pretrained("vamsibanda/sbert-all-MiniLM-L12-with-pooler")
 inputs = tokenizer("I love burritos!", return_tensors="pt")
 pred = model(**inputs)
-```
-You will also be able to leverage the pipeline API in transformers:
-```python
-from transformers import pipeline
-
-onnx_extractor = pipeline("feature-extraction", model=model, tokenizer=tokenizer)
-text = "I love burritos!"
-pred = onnx_extractor(text)
 ```