model.eval()の追加

app.py

@@ -25,6 +25,9 @@ tokenizer = T5Tokenizer.from_pretrained("rinna/japanese-gpt2-medium")
 # model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt2-medium")
 model = AutoModelForCausalLM.from_pretrained("output/")
 
+# 平均/分散の値を正規化
+model.eval()
+
 # 推論の実行
 #def Chat(prompt):
 #    input = tokenizer.encode(prompt, return_tensors="pt")