Update chatbot.py

chatbot.py

@@ -26,9 +26,9 @@ from gradio_client import Client, file
 from groq import Groq
 
 # You can also use models that are commented below
-model_id = "llava-hf/llava-interleave-qwen-0.5b-hf"
+# model_id = "llava-hf/llava-interleave-qwen-0.5b-hf"
 # model_id = "llava-hf/llava-interleave-qwen-7b-hf"
-# model_id = "llava-hf/llava-interleave-qwen-7b-dpo-hf"
+model_id = "llava-hf/llava-interleave-qwen-7b-dpo-hf"
 processor = LlavaProcessor.from_pretrained(model_id)
 model = LlavaForConditionalGeneration.from_pretrained(model_id,torch_dtype=torch.float16) #,  use_flash_attention_2=True)
 model.to("cpu")