Update app.py

app.py

@@ -13,8 +13,8 @@ example = [
     ['import java.util.*;\n\npublic class ehab4 {\n    public static void main( String[] args ) {\n        Scanner in = new Scanner( System.in );\n\tint a = 0, b = 0;\n\tSystem.out.println( "? 0 0 " );\n\tSystem.out.flush();\n\tint c = in.nextInt();\n\tfor ( int i = 29; i >= 0; i-- ) {\n\t    System.out.println( "? " + ( a + ( 1 << i ) ) + " " + b );\n\t    System.out.flush();\n\t    int q1 = in.nextInt();\n\t    System.out.println( "? " + a + " " + ( b + ( 1 << i ) ) );\n\t    System.out.flush();\n\t    int q2 = in.nextInt();\n\t    if ( q1 == q2 ) {\n\t\tif ( c == 1 )\n\t\t    a += ( 1 << i );\n\t\telse if ( c == -1 )\n\t\t    b += ( 1 << i );\n\t\tc = q1;\n\t    }\n\t    else if ( q1 == -1 ) {\n\t\ta += ( 1 << i );\n\t\tb += ( 1 << i );\n\t    }\n\t    else if ( q1 == -2 )\n\t\treturn;\n\t}\n\tSystem.out.println( "! " + a + " " + b );\n\tSystem.out.flush();\n    }\n}\n']]
 
 # model to be changed to the finetuned one
-tokenizer = AutoTokenizer.from_pretrained("codeparrot/codeparrot-small-complexity-prediction")
-model = AutoModelForSequenceClassification.from_pretrained("codeparrot/codeparrot-small-complexity-prediction", num_labels=7)
+tokenizer = AutoTokenizer.from_pretrained("codeparrot/unixcoder-java-complexity-prediction")
+model = AutoModelForSequenceClassification.from_pretrained("codeparrot/unixcoder-java-complexity-prediction", num_labels=7)
 
 def get_label(output):
     label = int(output[-1])