Update app.py

app.py

@@ -4,13 +4,15 @@ from transformers import AutoModelForSequenceClassification, pipeline
 import gradio as gr
 data = load_dataset("huolongguo10/insecure",split="train").shuffle(seed=42).select(range(1000))
 task_evaluator = evaluator("text-classification")
-model = AutoModelForSequenceClassification.from_pretrained("huolongguo10/check_sec").float()
+model = AutoModelForSequenceClassification.from_pretrained("huolongguo10/check_sec").half()
+tokenizer = AutoTokenizer.from_pretrained("huolongguo10/check_sec")
 # 1. Pass a model name or path
 eval_results = task_evaluator.compute(
     model_or_pipeline=model,
     data=data,
     input_column="sentence1",
-    label_mapping={"LABEL_0": 0, "LABEL_1": 1}
+    label_mapping={"LABEL_0": 0, "LABEL_1": 1},
+    tokenizer=tokenizer
 )
 
 with gr.Blocks() as demo: