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@@ -53,3 +53,16 @@ result = nlp(text)
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  for item in result:
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  print(item)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  for item in result:
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  print(item)
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+ ```
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+
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+ ## Citation
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+ If you use this model in your research or applications, please cite it as follows:
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+ ```
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+ @misc{keetawan2024aspectsentiment,
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+ author = {Keetawan Limaroon},
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+ title = {XLM-RoBERTa-Large for Aspect-Based Sentiment Analysis in Thai},
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+ year = {2024},
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+ publisher = {Hugging Face},
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+ url = {https://huggingface.co/Keetawan/xlm-roberta-large-aspect-based-sentiment},
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+ }
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+