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