Create app.py

app.py

@@ -0,0 +1,65 @@
+#V01
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Liste des modèles disponibles
+model_list = [
+    "fbaldassarri/tiiuae_Falcon3-1B-Instruct-autogptq-int8-gs128-asym",
+    "MisterAI/jpacifico_Chocolatine-3B-Instruct-DPO-v1.2",
+    # Ajoutez d'autres modèles ici
+]
+
+def load_model(model_name):
+    """Charge le modèle et le tokenizer"""
+    tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+    model = AutoModelForCausalLM.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"""
+    inputs = tokenizer(input_text, return_tensors="pt")
+    output = model.generate(**inputs, max_length=max_length, temperature=temperature)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+def main(model_name, input_text, max_length, temperature):
+    """Fonction principale pour générer le texte"""
+    model, tokenizer = load_model(model_name)
+    generated_text = generate_text(model, tokenizer, input_text, max_length, temperature)
+    return generated_text
+
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown("# Try It")
+    
+    with gr.Row():
+        model_select = gr.Dropdown(model_list, label="Sélectionner un modèle")
+        load_button = gr.Button("Charger le modèle")
+        
+    with gr.Row():
+        input_text = gr.Textbox(label="Texte d'entrée")
+        max_length_slider = gr.Slider(50, 500, label="Longueur maximale", value=200)
+        temperature_slider = gr.Slider(0.1, 1.0, label="Température", value=0.7)
+        submit_button = gr.Button("Soumettre")
+        
+    output_text = gr.Textbox(label="Texte généré")
+    history = gr.JSON(label="Historique")
+    
+    load_button.click(
+        load_model,
+        inputs=model_select,
+        outputs=None,
+        queue=False
+    )
+    
+    submit_button.click(
+        main,
+        inputs=[model_select, input_text, max_length_slider, temperature_slider],
+        outputs=output_text,
+        queue=False
+    )
+
+if __name__ == "__main__":
+    demo.launch()