use chat completions instead of base model syntax

README.md

@@ -194,12 +194,12 @@ Phi-4-mini-instruct is also available in [Azure AI Studio]()
 
 #### Example
  
-After obtaining the Phi-4-mini-instruct model checkpoints, users can use this sample code for inference.
+After obtaining the Phi-4-mini-instruct chat models, users can use this sample code for inference.
  
 ```python
 import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
- 
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
 torch.random.manual_seed(0)
 
 model_path = "microsoft/Phi-4-mini-instruct"
@@ -211,29 +211,30 @@ model = AutoModelForCausalLM.from_pretrained(
     trust_remote_code=True,
 )
 tokenizer = AutoTokenizer.from_pretrained(model_path)
- 
+
 messages = [
     {"role": "system", "content": "You are a helpful AI assistant."},
     {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
     {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
     {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
 ]
- 
-pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-)
- 
+
+# Prepare the input for the model
+input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
+
+# Generate the response
 generation_args = {
     "max_new_tokens": 500,
-    "return_full_text": False,
     "temperature": 0.0,
     "do_sample": False,
 }
- 
-output = pipe(messages, **generation_args)
-print(output[0]['generated_text'])
+
+output_ids = model.generate(input_ids, **generation_args)
+
+# Decode the generated tokens to text
+response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+print(response)
 ```
  
 ## Responsible AI Considerations