Added demo code according to the prompt format (#5)

- Added demo code according to the prompt format (add8a485bc64cab78ea36d93003a4fdc518a5f4a)


Co-authored-by: tim <[email protected]>

README.md

@@ -52,11 +52,36 @@ The following hyperparameters were used during training:
 
 ## Inference with transformers
 
-```shell
+```python
 import transformers
-model = transformers.AutoModelForCausalLM.from_pretrained(
-  'Intel/neural-chat-7b-v3-1'
-)
+
+
+model_name = 'Intel/neural-chat-7b-v3-1'
+model = transformers.AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
+
+
+def generate_response(system_input, user_input):
+    
+    # Format the input using the provided template
+    prompt = f"### System:\n{system_input}\n### User:\n{user_input}\n### Assistant:\n"
+
+    # Tokenize and encode the prompt
+    inputs = tokenizer.encode(prompt, return_tensors="pt")
+
+    # Generate a response
+    outputs = model.generate(inputs, max_length=1000, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Extract only the assistant's response
+    return response.split("### Assistant:\n")[-1]
+
+
+# Example usage
+system_input = "You are a chatbot developed by Intel. Please answer all questions to the best of your ability."
+user_input = "How does the neural-chat-7b-v3-1 model work?"
+response = generate_response(system_input, user_input)
+print(response)
 ```
 
 ## Ethical Considerations and Limitations