support RM metrics, add generating Args

Former-commit-id: c461c6190bc124e98dde7f3cf96a59ce40b26fb0

src/cli_demo.py

@@ -15,7 +15,7 @@ from transformers import TextIteratorStreamer
 
 def main():
 
-    model_args, data_args, finetuning_args = prepare_infer_args()
+    model_args, data_args, finetuning_args, generating_args = prepare_infer_args()
     model_name = "BLOOM" if "bloom" in model_args.model_name_or_path else "LLaMA"
     model, tokenizer = load_pretrained(model_args, finetuning_args)
 
@@ -25,17 +25,10 @@ def main():
     def predict_and_print(query, history: list):
         input_ids = tokenizer([prompt_template.get_prompt(query, history)], return_tensors="pt")["input_ids"]
         input_ids = input_ids.to(model.device)
-        gen_kwargs = {
-            "input_ids": input_ids,
-            "do_sample": True,
-            "top_p": 0.7,
-            "temperature": 0.95,
-            "num_beams": 1,
-            "max_new_tokens": 512,
-            "repetition_penalty": 1.0,
-            "logits_processor": get_logits_processor(),
-            "streamer": streamer
-        }
+        gen_kwargs = generating_args.to_dict()
+        gen_kwargs["input_ids"] = input_ids
+        gen_kwargs["logits_processor"] = get_logits_processor()
+        gen_kwargs["streamer"] = streamer
         thread = Thread(target=model.generate, kwargs=gen_kwargs)
         thread.start()
         response = ""