Update app.py

app.py

@@ -3,10 +3,10 @@ import numpy as np
 import gradio as gr
 import torch
 from transformers import AutoModelForMultipleChoice, AutoTokenizer
-from huggingface_hub import hf_hub_url, Repository
-model_id="deepset/deberta-v3-large-squad2"
-# Load the model and tokenizer
 
+model_id = "deepset/deberta-v3-large-squad2"
+
+# Load the model and tokenizer
 model = AutoModelForMultipleChoice.from_pretrained(model_id)
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 
@@ -28,12 +28,13 @@ def predict(data):
     predictions_as_ids = torch.argsort(-logits, dim=1)
     answers = np.array(list("ABCDE"))[predictions_as_ids.tolist()]
     return ["".join(i) for i in answers[:, :3]]
-
+text=gr.Textbox(placeholder="paste multiple choice questions.....")
+label=gr.Label(num_top_classes=3)
 # Create the Gradio interface
 iface = gr.Interface(
     fn=predict,
-    inputs=["text","checkbox",gr.Slider(0,100)],
-    outputs=["text","number"],
+    inputs=text  # Use the correct class with type="json"
+    outputs=label,
     live=True,
     examples=[
         {"prompt": "This is the prompt", "A": "Option A text", "B": "Option B text", "C": "Option C text", "D": "Option D text", "E": "Option E text"}
@@ -43,4 +44,4 @@ iface = gr.Interface(
 )
 
 # Run the interface
-iface.launch(share=True)
+iface.launch()