fix sft single turn inference example (#5416)

applications/Colossal-LLaMA-2/inference_example.py

@@ -15,7 +15,7 @@ def load_model(model_path, device="cuda", **kwargs):
     model.to(device)
 
     try:
-        tokenizer = AutoTokenizer.from_pretrained(model_path)
+        tokenizer = AutoTokenizer.from_pretrained(model_path, padding_side='left')
     except OSError:
         raise ImportError("Tokenizer not found. Please check if the tokenizer exists or the model path is correct.")
 
@@ -29,6 +29,7 @@ def generate(args):
     if args.prompt_style == "sft":
         conversation = default_conversation.copy()
         conversation.append_message("Human", args.input_txt)
+        conversation.append_message("Assistant", None)
         input_txt = conversation.get_prompt()
     else:
         BASE_INFERENCE_SUFFIX = "\n\n->\n\n"
@@ -46,7 +47,7 @@ def generate(args):
         num_return_sequences=1,
     )
     response = tokenizer.decode(output.cpu()[0, num_input_tokens:], skip_special_tokens=True)
-    logger.info(f"Question: {input_txt} \n\n Answer: \n{response}")
+    logger.info(f"\nHuman: {args.input_txt} \n\nAssistant: \n{response}")
     return response