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from transformers import pipeline
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import gradio as gr
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model_path="matiss/Latvian-Twitter-Sentiment-Analysis"
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sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
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def classify(text):
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output = sentiment_task(text)
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return output[0]['label'], output[0]['score']
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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textbox = gr.Textbox(label="Input text:", placeholder="Man garšo pankūkas ar kotletēm", lines=5)
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greet_btn = gr.Button("Classify")
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with gr.Column():
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outbox = gr.Textbox(label="Prediction:", placeholder="positive")
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runbox = gr.Textbox(label="Score")
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greet_btn.click(
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fn=classify,
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inputs=textbox,
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outputs=[outbox, runbox]
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)
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examples = gr.Examples(
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examples=[
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["Lietus šodien līst kā pa Jāņiem."],
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["Es neciešu pirmdienas"],
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["Pusdienās Tev jāēd brokolis, steiks, biezpiensieriņš un jāuzdzer Dlight."],
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["Nesaprotu vairs kas te tagad notiek"],
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["Man garšo pankūkas ar kotletēm"],
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],
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inputs=[textbox],
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)
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demo.launch() |
