add audio and classificator model

app.py

@@ -3,12 +3,15 @@ import requests
 from transformers import pipeline
 import tensorflow as tf
 
-inception_net = tf.keras.applications.MobileNetV2()
-
 # Obteniendo las labels de "https://git.io/JJkYN"
 respuesta = requests.get("https://raw.githubusercontent.com/gradio-app/mobilenet-example/master/labels.txt")
 etiquetas =respuesta.text.split("\n")
 
+# models
+trans = pipeline("automatic-speech-recognition", model = "facebook/wav2vec2-large-xlsr-53-spanish")
+clasificador = pipeline("text-classification", model = "pysentimiento/robertuito-sentiment-analysis")
+inception_net = tf.keras.applications.MobileNetV2()
+
 def clasifica_imagen(inp):
   inp = inp.reshape((-1,224,224,3))
   inp = tf.keras.applications.mobilenet_v2.preprocess_input(inp)