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