Update app.py

app.py

@@ -1,4 +1,4 @@
-#V01
+#V02
 
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
@@ -13,26 +13,15 @@ model_list = [
 
 
 
-
-model = None
-tokenizer = None
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
 def load_model(model_name):
     """Charge le modèle et le tokenizer"""
-    global model, tokenizer
-    model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
-    tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
-
-
-
-#def load_model(model_name):
-#    """Charge le modèle et le tokenizer"""
-#    if model_name is not None:
-#        tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
-#        model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
-#        return model, tokenizer
-#    else:
-#        return None, None
+    if model_name is not None and model_name!= "":
+        model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+        tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+        return model, tokenizer
 
 def generate_text(model, tokenizer, input_text, max_length, temperature):
     """Génère du texte en utilisant le modèle"""
@@ -42,7 +31,7 @@ def generate_text(model, tokenizer, input_text, max_length, temperature):
 
 def main(model_name, input_text, max_length, temperature):
     """Fonction principale pour générer le texte"""
-    if model_name is not None:
+    if model_name is not None and model_name!= "":
         model, tokenizer = load_model(model_name)
         generated_text = generate_text(model, tokenizer, input_text, max_length, temperature)
         return generated_text
@@ -72,14 +61,14 @@ with demo:
     
     load_button.click(
         load_model,
-        inputs=model_select,
+        inputs=model_name,
         outputs=None,
         queue=False
     )
     
     submit_button.click(
         main,
-        inputs=[model_select, input_text, max_length_slider, temperature_slider],
+        inputs=[model_name, input_text, max_length_slider, temperature_slider],
         outputs=output_text,
         queue=False
     )