Update app.py

app.py

@@ -11,7 +11,7 @@ import os
 #sft_model = "somosnlp/gemma-FULL-RAC-Colombia_v2"
 #sft_model = "somosnlp/RecetasDeLaAbuela_mistral-7b-instruct-v0.2-bnb-4bit"
 #base_model_name = "unsloth/Mistral-7B-Instruct-v0.2"
-sft_model = "somosnlp/RecetasDeLaAbuela_gemma-2b-it-bnb-4bit"
+sft_model1 = "somosnlp/RecetasDeLaAbuela_gemma-2b-it-bnb-4bit"
 sft_model2 = "somosnlp/RecetasDeLaAbuela_mistral-7b-instruct-v0.2-bnb-4bit"
 base_model_name = "unsloth/gemma-2b-it-bnb-4bit"
 
@@ -34,7 +34,7 @@ base_model = AutoModelForCausalLM.from_pretrained(base_model_name,return_dict=Tr
 #base_model = AutoModelForCausalLM.from_pretrained(base_model_name, return_dict=True, device_map = {"":0}, attn_implementation = attn_implementation,).eval()
 
 tokenizer = AutoTokenizer.from_pretrained(base_model_name, max_length = max_seq_length)
-ft_model = PeftModel.from_pretrained(base_model, sft_model)
+ft_model = PeftModel.from_pretrained(base_model, sft_model1)
 model = ft_model.merge_and_unload()
 model.save_pretrained(".")
 #model.to('cuda')
@@ -103,11 +103,11 @@ mis_ejemplos = [
     ["¿Como se cocinan unos autenticos frijoles?"],
 ]
 
-lista_modelos = [] "somosnlp/RecetasDeLaAbuela_gemma-2b-it-bnb-4bit", "somosnlp/RecetasDeLaAbuela_mistral-7b-instruct-v0.2-bnb-4bit"]
+lista_modelos = [sft_model1, sft_model2]
 
 iface = gr.Interface(
     fn=mostrar_respuesta,
-    inputs=[gr.Dropdown(lista_modelos, value = 0, label="Modelo", type="value"),
+    inputs=[gr.Dropdown(choices=lista_modelos, value = sft_model1, label="Modelo", type="value"),
         gr.Textbox(label="Pregunta"), 
         gr.Textbox(label="Contexto", value="You are a helpful AI assistant. Eres un experto cocinero hispanoamericano."),],
     outputs=[gr.Textbox(label="Respuesta", lines=2),],