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Update app.py
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app.py
CHANGED
@@ -1,34 +1,21 @@
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import gradio as gr
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from transformers import pipeline
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#trans = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-xlsr-53-spanish")
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classifier = pipeline("text-classification", model="pysentimiento/robertuito-sentiment-analysis")
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def audio_to_text(audio):
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text = trans(audio)["text"]
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return text
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def text_to_sentiment(text):
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return classifier(text)[0]
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demo = gr.Blocks()
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with demo:
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gr.Markdown("Demostración de análisis de sentimientos de textos")
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with gr.Tabs():
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#with gr.TabItem("Transcribe audio in Spanish"):
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# with gr.Row():
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# audio = gr.Audio(source="microphone", type="filepath")
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# transcription = gr.Textbox()
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# b1 = gr.Button("Transcribe")
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with gr.TabItem("Análisis de sentimientos de textos en español"):
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with gr.Row():
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texto = gr.Textbox()
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label = gr.Label(num_top_classes=1)
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b2.click(text_to_sentiment, inputs=texto, outputs=label)
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demo.launch()
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import gradio as gr
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from transformers import pipeline
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classifier = pipeline("text-classification", model="pysentimiento/robertuito-sentiment-analysis")
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def text_to_sentiment(text):
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return {classifier(text)[0]["label"]: classifier(text)[0]["score"]}
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demo = gr.Blocks()
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with demo:
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with gr.Tabs():
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with gr.TabItem("Análisis de sentimientos de textos en español"):
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with gr.Row():
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texto = gr.Textbox()
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label = gr.Label(num_top_classes=1)
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b1 = gr.Button("Analizar")
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b1.click(text_to_sentiment, inputs=texto, outputs=label)
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demo.launch()
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