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metadata
license: apache-2.0
language:
  - yo
  - en
metrics:
  - rouge
pipeline_tag: translation
tags:
  - text
  - machine-translation
  - language-translation
  - seq2seq
  - helsinki-nlp

Predicting English Translation

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# Loading tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("kingabzpro/Helsinki-NLP-opus-yor-mul-en")
model = AutoModelForSeq2SeqLM.from_pretrained("kingabzpro/Helsinki-NLP-opus-yor-mul-en").to('cuda')

# Prediction
a = model.generate(**tokenizer.prepare_seq2seq_batch('Nínú ìpè kan lẹ́yìn ìgbà náà, wọ́n sọ fún aṣojú iléeṣẹ́ BlaBlaCar pé ètò náà ti yí padà, pé',return_tensors='pt').to('cuda'))
text = tokenizer.batch_decode(a)

# Cleaning text
text = str(text)
text = re.sub("<pad> ","",text)
text = re.sub("'","",text)
text = text.replace("[", "")
text = text.replace("]", "")
text

Result

'In a statement after that hearing, the BualaCard’s representative was told that the event had changed, that he had turned up.'

ROGUE Score

0.3025