Update README.md

README.md

@@ -62,31 +62,15 @@ Users should validate outputs with certified medical professionals. This model i
 ## How to Get Started with the Model
 
 ```python
-
-import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_id = "InferenceLab/MediLlama-3.2"
-
-# Load tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    torch_dtype=torch.bfloat16
-)
-
-# Apply the chat template
-messages = [
-    {"role": "system", "content": "You are a helpful AI assistant."},
-    {"role": "user", "content": "What are the symptoms of diabetes?"},
-]
-prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-chat_input = tokenizer(prompt, return_tensors="pt").to(model.device)
-
-# Generate response
-chat_outputs = model.generate(**chat_input, max_new_tokens=500)
-response = tokenizer.decode(chat_outputs[0][chat_input['input_ids'].shape[-1]:], skip_special_tokens=True) # Decode only the response part
-print("\nAssistant Response:", response)
+model = AutoModelForCausalLM.from_pretrained("InferenceLab/MediLlama-3.2")
+tokenizer = AutoTokenizer.from_pretrained("InferenceLab/MediLlama-3.2")
+
+input_text = "What are the symptoms of diabetes?"
+inputs = tokenizer(input_text, return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0]))
 ````
 
 ## Training Details