Update README.md

README.md

@@ -77,11 +77,19 @@ print(code)
 ```
 
 ### A Test Example
-``````
-User Prompt: Write a Python program to implement K-Means clustering. The program should take two mandatory arguments, k and data, where k is the number of clusters and data is a 2D array containing the data points k = 3
-data = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]]
+```python
+User_Prompt = """Write a Python program to implement K-Means clustering. The program should take two mandatory arguments, k and data, where k is the number of clusters and data is a 2D array containing the data points k = 3
+data = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]]"""
 
-Generated Output: Write a Python program to implement K-Means clustering. The program should take two mandatory arguments, k and data, where k is the number of clusters and data is a 2D array containing the data points k = 3
+inputs = tokenizer(User_Prompt, return_tensors="pt").input_ids.to('cuda')
+outputs = model.generate(inputs, max_new_tokens=500, do_sample=False, num_beams=1)
+python_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print("Generated Output:",python_code)
+>>>
+```
+``````
+Write a Python program to implement K-Means clustering. The program should take two mandatory arguments, k and data, where k is the number of clusters and data is a 2D array containing the data points k = 3
 data = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]] Ready for action! Let's do this! ```python
 import numpy as np