alter rewards data type

Former-commit-id: 3eb7eb2d37525da50fe401ab7c59532e6e1ef984

src/web_demo.py

@@ -7,21 +7,23 @@ import torch
 import mdtex2html
 import gradio as gr
 
-from utils import ModelArguments, load_pretrained
+from utils import ModelArguments, FinetuningArguments, load_pretrained
 from transformers import HfArgumentParser
 from transformers.utils.versions import require_version
 
 
 require_version("gradio==3.27.0", "To fix: pip install gradio==3.27.0") # higher version may cause problems
-parser = HfArgumentParser(ModelArguments)
-model_args, = parser.parse_args_into_dataclasses()
-model, tokenizer = load_pretrained(model_args)
+parser = HfArgumentParser((ModelArguments, FinetuningArguments))
+model_args, finetuning_args = parser.parse_args_into_dataclasses()
+model, tokenizer = load_pretrained(model_args, finetuning_args)
+
 if torch.cuda.device_count() > 1:
     from accelerate import dispatch_model, infer_auto_device_map
     device_map = infer_auto_device_map(model)
     model = dispatch_model(model, device_map)
 else:
     model = model.cuda()
+
 model.eval()
 
 
@@ -74,10 +76,10 @@ def parse_text(text): # copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT
 
 
 def format_example(query):
-        prompt = "Below is an instruction that describes a task. "
-        prompt += "Write a response that appropriately completes the request.\n"
-        prompt += "Instruction:\nHuman: {}\nAssistant: ".format(query)
-        return prompt
+    prompt = "Below is an instruction that describes a task. "
+    prompt += "Write a response that appropriately completes the request.\n"
+    prompt += "Instruction:\nHuman: {}\nAssistant: ".format(query)
+    return prompt
 
 
 def predict(input, chatbot, max_length, top_p, temperature, history):