explicit cot 20 digits

app.py

@@ -11,7 +11,7 @@ tokenizer = AutoTokenizer.from_pretrained(implicit_cot_model_name)
 no_cot_model_name = 'yuntian-deng/gpt2-no-cot-multiplication'
 no_cot_model = AutoModelForCausalLM.from_pretrained(no_cot_model_name)
 
-explicit_cot_model_name = 'yuntian-deng/gpt2-explicit-cot-multiplication'
+explicit_cot_model_name = 'yuntian-deng/gpt2-explicit-cot-multiplication-20-digits'
 explicit_cot_model = AutoModelForCausalLM.from_pretrained(explicit_cot_model_name)
 
 models = {'implicit': implicit_cot_model, 'no': no_cot_model, 'explicit': explicit_cot_model}
@@ -20,7 +20,8 @@ models = {'implicit': implicit_cot_model, 'no': no_cot_model, 'explicit': explic
 [model.eval() for model in models.values()]
 
 # Constants
-MAX_PRODUCT_DIGITS_PER_MODEL = {'implicit': 100, 'no': 100, 'explicit': 960}
+#MAX_PRODUCT_DIGITS_PER_MODEL = {'implicit': 100, 'no': 100, 'explicit': 960}
+MAX_PRODUCT_DIGITS_PER_MODEL = {'implicit': 100, 'no': 100, 'explicit': 1070}
 
 def preprocess(num):
     num = str(num).strip().replace(' ', '')