made the output in table format

app.py

@@ -2,6 +2,7 @@ from transformers import AutoModelForSequenceClassification,AutoTokenizer
 from torch.nn.functional import softmax
 import torch
 import gradio as gr
+import json
 
 model_name="nebiyu29/hate_classifier"
 tokenizer=AutoTokenizer.from_pretrained(model_name)
@@ -20,16 +21,26 @@ def model_classifier(text):
             probs_label=softmax(logits,dim=-1)  #turning the probability distribution into normalize form
             id2label=model.config.id2label
             return_probs={id2label[i]:probs.item() for i,probs in enumerate(probs_label[0])}
-            return return_probs
+            return json.dumps(list(return_probs.items()))
 
 
 
 
+#lets define how the output looks like
+output_format=gr.Table(label="label probabilities",
+                      columns=["label","probabilities"],
+                       type="table",
+                       show_index=False,
+                       input_type="json",
+                       max_rows=4,
+                       max_columms=2
+                      )
+            
 #lets write something that accepts input as text and returns the most likely out come out of 3
 demo=gr.Interface(
     fn=model_classifier,
     inputs=gr.Textbox(lines=5,label="Enter you text"),
-    outputs=gr.Textbox(lines=5,label="Label scores"),
+    outputs=output_format,
     title="Hate Classifier Demo App"
 )
 demo.launch(share=True)