Update README.md

README.md

@@ -75,6 +75,31 @@ Clinical Mosaic was pre-trained on deidentified clinical notes from MIMIC-IV-NOT
 
 Install the Hugging Face Transformers library and load the model as follows:
 
+### For embeddings generation:
+
+```python
+from transformers import AutoModel, BertTokenizer, BertConfig
+
+tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') # MosaicBERT uses the standard BERT tokenizer
+config = BertConfig.from_pretrained('Sifal/ClinicalMosaic') # the config needs to be passed in
+
+ClincalMosaic = AutoModel.from_pretrained(
+    'Sifal/ClinicalMosaic',
+    config=config,
+    torch_dtype='auto',
+    trust_remote_code=True,
+    device_map="auto"
+)
+
+# Example usage
+clinical_text = "..."
+
+inputs = tokenizer(clinical_text, return_tensors="pt")
+last_layer_embeddings = ClincalMosaic(**inputs, output_all_encoded_layers=False)
+```
+
+### For sequence classification:
+
 ```python
 from transformers import AutoModelForSequenceClassification, BertTokenizer, BertConfig