Update README.md

README.md

@@ -59,9 +59,8 @@ Here is how to use this model to extract radiological sentence embeddings and ob
 ```python
 # Load the model and tokenizer
 url = "microsoft/BiomedVLP-CXR-BERT-specialized"
-config = AutoConfig.from_pretrained(url, use_auth_token=True, trust_remote_code=True)
-tokenizer = AutoTokenizer.from_pretrained(url, use_auth_token=True, trust_remote_code=True)
-model = AutoModel.from_pretrained(url, config=config, use_auth_token=True, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(url, trust_remote_code=True)
+model = AutoModel.from_pretrained(url, trust_remote_code=True)
 
 # Input text prompts (e.g., reference, synonym, contradiction)
 text_prompts = ["There is no pneumothorax or pleural effusion",