Update README.md

README.md

@@ -288,7 +288,6 @@ Here are examples of how to run and sample from the model.
 
 ## Generic generaion
 ```python
-import json
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
 example = """
@@ -338,18 +337,23 @@ print("### Prediction")
 print(tokenizer.decode(out[0][input_len:]))
 ```
 
-## Fill in the middle generation
+## Fill in the middle with additional files as context generation
 ```python
-prefix = """
-def fibonacci(n: int) -> int:
-"""
-
-suffix = """
-if __name__ == "__main__":
-    print(fibonacci(10))
-"""
+example = """<filename>utils.py
+def multiply(x, y):
+    return x * y
+<filename>config.py
+DEBUG = True
+MAX_VALUE = 100
+<filename>example.py
+<fim_suffix> 
+
+# Test the function
+result = calculate_sum(5, 10)
+print(result)<fim_prefix>def calculate_sum(a, b):
+<fim_middle>"""
 
-encoded_input = tokenizer(f"<fim_suffix>{suffix}<fim_prefix>{prefix}<fim_middle>", return_tensors='pt', return_token_type_ids=False)
+encoded_input = tokenizer(example, return_tensors='pt', return_token_type_ids=False)
 out = model.generate(
     **encoded_input,
     max_new_tokens=100,