Update app.py

app.py

@@ -1,23 +1,24 @@
 import gradio as gr
-from transformers import AutoTokenizer, T5ForConditionalGeneration
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import torch
 
-model_name = "DenoKuso/t5-small-gec-fr"
+# Utilisation du modèle sdadas/byt5-text-correction
+model_name = "sdadas/byt5-text-correction"
 
 tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = T5ForConditionalGeneration.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model.to(device)
 
 def correction_grammaticale(texte):
-    # Ce modèle utilise (a priori) le préfixe "gec: " pour la correction.
-    input_text = "gec: " + texte
+    # Pour le français, on ajoute le préfixe "<fr>" devant le texte
+    input_text = "<fr> " + texte
     input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)
     
     outputs = model.generate(
         input_ids,
-        max_length=128,
+        max_length=512,
         num_beams=4,
         early_stopping=True
     )