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@@ -59,6 +59,10 @@ The primary intended use is to support AI researchers building on top of this wo
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  Here is how to use this model to extract radiological sentence embeddings and obtain their cosine similarity in the joint space (image and text):
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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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  Here is how to use this model to extract radiological sentence embeddings and obtain their cosine similarity in the joint space (image and text):
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  ```python
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+ import torch
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+
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+ from transformers import AutoModel, AutoTokenizer
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+
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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)