Update README.md

README.md

@@ -32,6 +32,50 @@ model = AutoPeftModelForCausalLM.from_pretrained(peft_model_id,
                                                  load_in_4bit=True)
 
 tokenizer = AutoTokenizer.from_pretrained(peft_model_id)
+
+tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "search_restaurants",
+            "description": "Search for restaurants in a specific location",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "location": {
+                        "type": "string",
+                        "description": "The location to search for restaurants"
+                    },
+                    "cuisine": {
+                        "type": "string",
+                        "description": "The cuisine type to filter the restaurants"
+                    },
+                    "price_range": {
+                        "type": "integer",
+                        "description": "The price range of the restaurants (1 = cheap to 4 = very expensive)"
+                    }
+                },
+                "required": ["location"]
+            }
+        }
+    }
+]
+
+messages=[
+        {"role": "user", "content": "I'm in Malappuram, can you find a restaurant for me?"}
+    ]
+
+prompt = tokenizer.apply_chat_template(
+    messages,
+    tools=tools,
+    add_generation_prompt=True,
+    tokenize=True,
+    return_tensors="pt"
+).to('cuda')
+
+output = model.generate(prompt, max_new_tokens=500)
+
+print(''.join(tokenizer.batch_decode(output[0][len(prompt[0]):])))
 ```
 
 ## Training procedure