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language: |
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- id |
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--- |
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# Paraphrase Generation with IndoT5 Base |
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IndoT5-base trained on translated PAWS. |
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## Model in action |
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```python |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("Wikidepia/IndoT5-base-paraphrase") |
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model = AutoModelForSeq2SeqLM.from_pretrained("Wikidepia/IndoT5-base-paraphrase") |
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sentence = "Anak anak melakukan piket kelas agar kebersihan kelas terjaga" |
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text = "paraphrase: " + sentence + " </s>" |
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encoding = tokenizer(text, padding='longest', return_tensors="pt") |
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outputs = model.generate( |
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input_ids=encoding["input_ids"], attention_mask=encoding["attention_mask"], |
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max_length=512, |
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do_sample=True, |
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top_k=200, |
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top_p=0.95, |
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early_stopping=True, |
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num_return_sequences=5 |
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) |
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``` |
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## Limitations |
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Sometimes paraphrase contain date which doesnt exists in the original text :/ |
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## Acknowledgement |
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Thanks to Tensorflow Research Cloud for providing TPU v3-8s. |
