Update README.md

README.md

@@ -19,7 +19,7 @@ Load the pretrained AITSecNER model directly from Hugging Face:
 ```python
 from gliner import GLiNER
 
-model = GLiNER.from_pretrained(\"selfconstruct3d/AITSecNER\", load_tokenizer=True)
+model = GLiNER.from_pretrained("selfconstruct3d/AITSecNER", load_tokenizer=True)
 ```
 
 ### Predict Entities
@@ -28,10 +28,10 @@ Define the input text and entity labels you wish to extract:
 
 ```python
 # Example input text
-text = \"\"\"
+text = """
 Upon opening Emotet maldocs, victims are greeted with fake Microsoft 365 prompt that states 
 “THIS DOCUMENT IS PROTECTED,” and instructs victims on how to enable macros.
-\"\"\"
+"""
 
 # Entity labels
 labels = [
@@ -44,7 +44,7 @@ entities = model.predict_entities(text, labels, threshold=0.5)
 
 # Display results
 for entity in entities:
-    print(f\"{entity['text']} => {entity['label']}\")
+    print(f"{entity['text']} => {entity['label']}")
 ```
 
 ### Sample Output