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Browse files- README.md +17 -14
- app.py +42 -0
- requirements.txt +4 -0
README.md
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---
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title: Zero
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colorFrom:
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colorTo: yellow
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sdk: gradio
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---
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title: "Clasificación Zero-Shot en Español"
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emoji: "📝"
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colorFrom: "green"
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colorTo: "yellow"
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sdk: "gradio"
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short_description: "Clasifica texto en categorías personalizadas."
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models:
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- "Recognai/bert-base-spanish-wwm-cased-xnli"
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tags:
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- "zero-shot-classification"
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- "nlp"
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- "spanish"
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- "transformers"
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- "gradio"
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sdk_version: 5.21.0
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---
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app.py
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from transformers import pipeline
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import gradio as gr
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classifier = pipeline(
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"zero-shot-classification",
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model="Recognai/bert-base-spanish-wwm-cased-xnli"
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)
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def zero_shot_classification(text, labels):
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candidate_labels = [label.strip() for label in labels.split(",")] # Convertir en lista
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result = classifier(text, candidate_labels)
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output = "\n".join(
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[f"{label}: {score:.2f}" for label, score in zip(result['labels'], result['scores'])]
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)
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return output
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with gr.Blocks() as demo:
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gr.Markdown("""
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# Clasificación Zero-Shot en Español
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Esta aplicación permite clasificar un texto en diferentes categorías de tu elección.
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Solo debes proporcionar el texto y las etiquetas que deseas evaluar, y el modelo asignará probabilidades a cada una de ellas.
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""")
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gr.Interface(
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fn=zero_shot_classification,
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inputs=[
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gr.Textbox(label="Texto a clasificar", placeholder="Escribe el texto aquí..."),
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gr.Textbox(label="Etiquetas de clasificación", placeholder="Ejemplo: cultura, sociedad, economia, salud, deportes")
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],
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outputs=gr.Textbox(label="Resultados"),
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)
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gr.Markdown("""
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---
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Demostración de clasificación Zero-Shot usando el modelo [Recognai/bert-base-spanish-wwm-cased-xnli](https://huggingface.co/Recognai/bert-base-spanish-wwm-cased-xnli).
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Desarrollado con ❤️ por [@srjosueaaron](https://www.instagram.com/srjosueaaron/).
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""")
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if __name__ == "__main__":
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demo.launch()
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requirements.txt
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gradio
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transformers[sentencepiece]
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tensorflow
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tf-keras
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