marianmt-th-zh_cn

  • source languages: th
  • target languages: zh_cn
  • dataset:
  • model: transformer-align
  • pre-processing: normalization + SentencePiece
  • test set translations:
  • test set scores:

Training

Training scripts from LalitaDeelert/NLP-ZH_TH-Project. Experiments tracked at cstorm125/marianmt-th-zh_cn.

export WANDB_PROJECT=marianmt-th-zh_cn
python train_model.py --input_fname ../data/v1/Train.csv \
    --output_dir ../models/marianmt-th-zh_cn \
    --source_lang th --target_lang zh \
    --metric_tokenize zh --fp16

Usage

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
tokenizer = AutoTokenizer.from_pretrained("cstorm125/marianmt-zh_cn-th")
model = AutoModelForSeq2SeqLM.from_pretrained("cstorm125/marianmt-zh_cn-th").cpu()

src_text = [
    'ฉันรักคุณ',
    'ฉันอยากกินข้าว',
]
translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
print([tokenizer.decode(t, skip_special_tokens=True) for t in translated])

> ['我爱你', '我想吃饭。']

Requirements

transformers==4.6.0
torch==1.8.0
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