subir demo

model: facebook/wav2vec2-large-xlsr-53-spanish")
model : "pysentimiento/robertuito-sentiment-analysis")

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+from transformers import pipeline
+
+trans = pipeline("automatic-speech-recognition", model = "facebook/wav2vec2-large-xlsr-53-spanish")
+clasificador = pipeline("text-classification", model = "pysentimiento/robertuito-sentiment-analysis")
+
+def audio_a_text(audio):
+  text = trans(audio)["text"]
+  return text
+
+def texto_a_sentimiento(text):
+  return clasificador(text)[0]["label"]
+
+demo = gr.Blocks()
+
+with demo:
+  gr.Markdown("Demo para la clase de Platzi")
+  audio = gr.Audio(sources="microphone", type="filepath")
+  texto = gr.Textbox()
+  b1 = gr.Button("Transcribe porfa")
+  b1.click(audio_a_text, inputs=audio, outputs=texto)
+
+  b2 = gr.Button("Clasifica porfa el sentimiento")
+  label = gr.Label()
+  b2.click(texto_a_sentimiento, inputs=texto, outputs=label)
+
+demo.launch()