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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() |