Update app.py

app.py

@@ -5,6 +5,9 @@ from transformers import pipeline
 from transformers import LlamaTokenizer, LlamaForCausalLM
 import time
 import csv
+import locale
+locale.getpreferredencoding = lambda: "UTF-8"
+
 #https://huggingface.co/shibing624/chinese-alpaca-plus-7b-hf
 #https://huggingface.co/ziqingyang/chinese-alpaca-2-7b
 #https://huggingface.co/minlik/chinese-alpaca-plus-7b-merged
@@ -21,7 +24,7 @@ tokenizer = LlamaTokenizer.from_pretrained('shibing624/chinese-alpaca-plus-7b-hf
 pipeline = pipeline(
     "text-generation",
     model="shibing624/chinese-alpaca-plus-7b-hf",
-    torch_dtype=torch.float16,
+    torch_dtype=torch.float32,
     device_map="auto",
 )
 
@@ -35,7 +38,7 @@ user_input = st.text_input("")
 
 with open('alpaca_output.csv', 'a', newline='',encoding = "utf-8") as csvfile:
     writer = csv.writer(csvfile)
-    writer.writerow(["stockname",'prompt','answer','time'])
+    # writer.writerow(["stockname",'prompt','answer','time'])
     if user_input:
         if user_input[0] == ".":
             stockname = user_input[1:4]
@@ -67,6 +70,7 @@ with open('alpaca_output.csv', 'a', newline='',encoding = "utf-8") as csvfile:
             for seq in sequences:
                 st.write(f"Result: {seq}") #seq['generated_text']
             st.write(f"time: {(end-start):.2f}")
+            writer.writerow([stockname,text,sequences,f"time: {(end-start):.2f}"])
         
             # input_ids = tokenizer.encode(prompt, return_tensors='pt').to('cuda')
             # with torch.no_grad():
@@ -92,3 +96,4 @@ with open('alpaca_output.csv', 'a', newline='',encoding = "utf-8") as csvfile:
             for seq in sequences:
                 st.write(f"Result: {seq}") #seq['generated_text']
             st.write(f"time: {(end-start):.2f}")
+            writer.writerow(["無",user_input,sequences,f"time: {(end-start):.2f}"])