Update README.md

README.md

@@ -123,9 +123,18 @@ To generate from images use the below code after loading the model as shown abov
 import requests
 from PIL import Image
 
-prompt = "USER: <image>\nWhat are these?\nASSISTANT:"
-image_file = "http://images.cocodataset.org/val2017/000000039769.jpg"
+conversation = [
+    {
+      "role": "user",
+      "content": [
+          {"type": "text", "text": "What are these?"},
+          {"type": "image"},
+        ],
+    },
+]
+prompt = processor.apply_chat_template(conversation, add_generation_prompt=True)
 
+image_file = "http://images.cocodataset.org/val2017/000000039769.jpg"
 raw_image = Image.open(requests.get(image_file, stream=True).raw)
 inputs_image = processor(prompt, images=raw_image, return_tensors='pt').to(0, torch.float16)
 
@@ -142,7 +151,7 @@ conversation_1 = [
     {
       "role": "user",
       "content": [
-          {"type": "text", "text": "What's the content of the image"},
+          {"type": "text", "text": "What's the content of the image>"},
           {"type": "image"},
         ],
     }
@@ -156,8 +165,8 @@ conversation_2 = [
         ],
     },
 ]
-prompt_1 = processor.apply_chat_template(conversation, add_generation_prompt=True)
-prompt_2 = processor.apply_chat_template(conversation, add_generation_prompt=True)
+prompt_1 = processor.apply_chat_template(conversation_1, add_generation_prompt=True)
+prompt_2 = processor.apply_chat_template(conversation_2, add_generation_prompt=True)
 
 s = processor(text=[prompt_1, prompt_2], images=image, videos=clip, padding=True, return_tensors="pt").to(model.device)