changed the input to the model so that it can become in input ids and attention mask

app.py

@@ -16,8 +16,11 @@ def model_classifier(text):
         if len(text)==0:
             return f"the input text is {text}"
         else:
-            encoded_input=tokenizer(text) #this is where the encoding happens
-            logits=model(encoded_input).logits  #this is the logits of the labels
+            encoded_input=tokenizer(text,return_tensors="pt",truncation,padding=True,) #this is where the encoding happens
+            input_ids=encoded_input["input_ids"]
+            attention_mask=encoded_input["attention_mask"]
+            
+            logits=model(input_ids,attention_mask).logits  #this is the logits of the labels
             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])}