wiraindrak commited on
Commit
7f68476
1 Parent(s): d961c51

Update app.py

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Files changed (1) hide show
  1. app.py +20 -8
app.py CHANGED
@@ -2,28 +2,40 @@ from transformers import pipeline
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  import gradio as gr
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- pretrained_name = "w11wo/indonesian-roberta-base-sentiment-classifier"
 
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- sentiment = pipeline(
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  "sentiment-analysis",
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- model=pretrained_name,
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- tokenizer=pretrained_name,
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  return_all_scores=True
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  )
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  examples = [
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  "Masyarakat sangat kecewa dengan tragedi Kanjuruhan",
 
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  ]
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  def sentiment_analysis(text):
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- output = sentiment(text)
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  return {elm["label"]: elm["score"] for elm in output[0]}
 
 
 
 
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  demo = gr.Interface(
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- fn=sentiment_analysis,
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  inputs=gr.Textbox(placeholder="Enter a sentence here..."),
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- outputs="label",
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- interpretation="default",
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  examples=[examples])
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  if __name__ == "__main__":
 
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  import gradio as gr
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+ pretrained_sentiment = "w11wo/indonesian-roberta-base-sentiment-classifier"
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+ pretrained_ner = "cahya/bert-base-indonesian-NER"
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+ sentiment_pipeline = pipeline(
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  "sentiment-analysis",
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+ model=pretrained_sentiment,
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+ tokenizer=pretrained_sentiment,
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  return_all_scores=True
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  )
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+ ner_pipeline = pipeline(
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+ "ner",
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+ model=pretrained_ner,
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+ tokenizer=pretrained_ner
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+ )
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+
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  examples = [
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  "Masyarakat sangat kecewa dengan tragedi Kanjuruhan",
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+ "Jokowi mengutuk kepolisian atas kerusuhan yang terjadi di Malang"
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  ]
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  def sentiment_analysis(text):
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+ output = sentiment_pipeline(text)
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  return {elm["label"]: elm["score"] for elm in output[0]}
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+
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+ def ner(text):
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+ output = ner_pipeline(text)
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+ return {"text": text, "entities": output}
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  demo = gr.Interface(
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+ fn=[sentiment_analysis, ner],
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  inputs=gr.Textbox(placeholder="Enter a sentence here..."),
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+ outputs=["label", gr.HighlightedText()],
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+ interpretation=["default"],
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  examples=[examples])
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  if __name__ == "__main__":