update tokenizer

app.py

@@ -37,22 +37,22 @@ def get_image_gen_pipeline():
 def get_text_gen_pipeline():
     global _text_gen_pipeline
     if _text_gen_pipeline is None:
-        try:
-            device = "cuda" if torch.cuda.is_available() else "cpu"
-            tokenizer = AutoTokenizer.from_pretrained(
-                "mistralai/Mistral-7B-Instruct-v0.3",
-                use_fast=True  # Ensure fast tokenizer
-            )
-            _text_gen_pipeline = pipeline(
-                "text-generation",
-                model="mistralai/Mistral-7B-Instruct-v0.3",
-                tokenizer=tokenizer,
-                max_new_tokens=2048,
-                device=device,
-            )
-        except Exception as e:
-            print(f"Error loading text generation model: {e}")
-            return None
+         try:
+              device = "cuda" if torch.cuda.is_available() else "cpu"
+              tokenizer = AutoTokenizer.from_pretrained(
+                  "mistralai/Mistral-7B-Instruct-v0.3",
+                  use_fast=True  # Force l'utilisation du tokenizer rapide
+              )
+              _text_gen_pipeline = pipeline(
+                   "text-generation",
+                   model="mistralai/Mistral-7B-Instruct-v0.3",
+                   tokenizer=tokenizer,  # Utilise le tokenizer rapide
+                   max_new_tokens=2048,
+                   device=device,
+              )
+         except Exception as e:
+              print(f"Error loading text generation model: {e}")
+              return None
     return _text_gen_pipeline
 
 @spaces.GPU()
@@ -146,22 +146,15 @@ def preload_models():
     try:
         # Préchargement du modèle de génération de texte
         device = "cuda" if torch.cuda.is_available() else "cpu"
-        tokenizer = AutoTokenizer.from_pretrained(
-            "mistralai/Mistral-7B-Instruct-v0.3",
-            use_fast=True
-        )
-        global _text_gen_pipeline
         _text_gen_pipeline = pipeline(
             "text-generation",
             model="mistralai/Mistral-7B-Instruct-v0.3",
-            tokenizer=tokenizer,
             max_new_tokens=2048,
             device=device,
         )
         
         # Préchargement du modèle de génération d'images
         dtype = torch.bfloat16
-        global _image_gen_pipeline
         _image_gen_pipeline = DiffusionPipeline.from_pretrained(
             "black-forest-labs/FLUX.1-schnell",
             torch_dtype=dtype