added padding and truncation to tokenizer

app.py

@@ -1,5 +1,9 @@
 import gradio as gr
-
+import torch
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import Trainer, TrainingArguments, EarlyStoppingCallback
+barthez_tokenizer = AutoTokenizer.from_pretrained("moussaKam/barthez")
+model = AutoModelForSequenceClassification.from_pretrained("Anvil-ML/detecteur-ia")
 
 def interpret_pred(pred):
     low_bond = -6.748472
@@ -30,15 +34,9 @@ def interpret_pred_with_sensibility(pred):
 
 
 def main(text_sentence):
-    import torch
-    from transformers import AutoTokenizer, AutoModelForSequenceClassification
-    from transformers import Trainer, TrainingArguments, EarlyStoppingCallback
-
-    barthez_tokenizer = AutoTokenizer.from_pretrained("moussaKam/barthez")
-    model = AutoModelForSequenceClassification.from_pretrained("Anvil-ML/detecteur-ia")
 
     input_ids = torch.tensor(
-        [barthez_tokenizer.encode(text_sentence, add_special_tokens=True)]
+        [barthez_tokenizer.encode(text_sentence, truncation=True, padding=True, add_special_tokens=True)]
     )
 
     predict = model.forward(input_ids)[0]