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marianmt-zh_cn-th
cstorm125/marianmt-zh_cn-th
marianmt-zh_cn-th is a translation model from cstorm125. Use it when you need text moved from one language to another. It is set up for transformers.
source languages: zhcn target languages: th dataset: model: transformer-align pre-processing: normalization + SentencePiece test set translations: test set scores:
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At a glance
- Task
- Translation
- Library
- transformers
- Model type
- marian
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jun 23, 2021
- SHA
- c267114f
Try a prompt
Model card
From the Hugging Face model README
marianmt-zh_cn-th
- source languages: zh_cn
- target languages: th
- 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-zh_cn-th.
export WANDB_PROJECT=marianmt-zh_cn-th
python train_model.py --input_fname ../data/v1/Train.csv \
\\t--output_dir ../models/marianmt-zh_cn-th \
\\t--source_lang zh --target_lang th \
\\t--metric_tokenize th_syllable --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 = [
'我爱你',
'我想吃米饭',
]
translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
print([tokenizer.decode(t, skip_special_tokens=True) for t in translated])
> ['ผมรักคุณนะ', 'ฉันอยากกินข้าว']
Requirements
transformers==4.6.0
torch==1.8.0
- Task
- Translation
- Library
- transformers
- Type
- marian
- Created
- Mar 2, 2022
- Updated
- Jun 23, 2021