Instructions to use ILT37/en_to_vi_translation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ILT37/en_to_vi_translation with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ILT37/en_to_vi_translation") model = AutoModelForSeq2SeqLM.from_pretrained("ILT37/en_to_vi_translation") - Notebooks
- Google Colab
- Kaggle
State-of-the-art English-Vietnamese and Vietnamese-English Translation models trained on MTet, PhoMT.
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
model_name = "ILT37/en_to_vo_translation"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
inputs = [
"vi: Theo báo cáo mới nhất của Linkedin về danh sách việc làm triển vọng với mức lương hấp dẫn năm 2020, các chức danh công việc liên quan đến AI như Chuyên gia AI (Artificial Intelligence Specialist), Kỹ sư ML (Machine Learning Engineer) đều xếp thứ hạng cao.",
"en: I go to school",
"en: ... is girlfriend of me"
]
outputs = model.generate(tokenizer(inputs, return_tensors="pt", padding=True).input_ids.to('cuda'), max_length=512)
print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
- Downloads last month
- 3
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support