Update app.py

app.py

@@ -5,8 +5,8 @@ import pytube as pt
 from transformers import pipeline
 from huggingface_hub import model_info
 
-MODEL_NAME = "openai/whisper-small" #this always needs to stay in line 8 :D sorry for the hackiness
-lang = "en"
+MODEL_NAME = "openai/whisper-small" #Ésto es la base de con lo que trabaja el script entonces hay que cargarlo en la linea 8.
+lang = "es"
 
 device = 0 if torch.cuda.is_available() else "cpu"
 pipe = pipeline(
@@ -22,12 +22,12 @@ def transcribe(microphone, file_upload):
     warn_output = ""
     if (microphone is not None) and (file_upload is not None):
         warn_output = (
-            "WARNING: You've uploaded an audio file and used the microphone. "
-            "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
+            "Consejo: Subiste un Archivo de Audio y usado el micrófono. "
+            "el Archivo Grabado del Microfono Local será enviado a Analizar. OK!\n"
         )
 
     elif (microphone is None) and (file_upload is None):
-        return "ERROR: You have to either use the microphone or upload an audio file"
+        return "Advertencia: Tu tienes los 2 usa el Micrófono o un archivo subido desde tu PC."
 
     file = microphone if microphone is not None else file_upload
 
@@ -67,9 +67,9 @@ mf_transcribe = gr.Interface(
     outputs="text",
     layout="horizontal",
     theme="huggingface",
-    title="Whisper Demo: Transcribe Audio",
+    title="Escucha",
     description=(
-        "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the the fine-tuned"
+        "Transcribe Largas capturas de audio de Radio 160.310 Mgh por micrófono o grabaciones desde archivos a 1 click y gratis! Ésta version está utilizando por defecto fine-tuned para el mejor aprovechamiento del contexto."
         f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
         " of arbitrary length."
     ),
@@ -82,9 +82,9 @@ yt_transcribe = gr.Interface(
     outputs=["html", "text"],
     layout="horizontal",
     theme="huggingface",
-    title="Whisper Demo: Transcribe YouTube",
+    title="Escucha: Transcribe los videos de YouTube",
     description=(
-        "Transcribe long-form YouTube videos with the click of a button! Demo uses the the fine-tuned checkpoint:"
+        "Transcribe Largas capturas de audio de Radio 160.310 Mgh por micrófono o grabaciones desde archivos a 1 click y gratis! Ésta version está utilizando por defecto fine-tuned para el mejor aprovechamiento del contexto."
         f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of"
         " arbitrary length."
     ),