Instructions to use vinai/vinai-translate-vi2en-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vinai/vinai-translate-vi2en-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("vinai/vinai-translate-vi2en-v2") model = AutoModelForMultimodalLM.from_pretrained("vinai/vinai-translate-vi2en-v2") - Notebooks
- Google Colab
- Kaggle
A Vietnamese-English Neural Machine Translation System
Our pre-trained VinAI Translate models are state-of-the-art text translation models for Vietnamese-to-English and English-to-Vietnamese, respectively. The general architecture and experimental results of VinAI Translate can be found in our paper:
@inproceedings{vinaitranslate,
title = {{A Vietnamese-English Neural Machine Translation System}},
author = {Thien Hai Nguyen and
Tuan-Duy H. Nguyen and
Duy Phung and
Duy Tran-Cong Nguyen and
Hieu Minh Tran and
Manh Luong and
Tin Duy Vo and
Hung Hai Bui and
Dinh Phung and
Dat Quoc Nguyen},
booktitle = {Proceedings of the 23rd Annual Conference of the International Speech Communication Association: Show and Tell (INTERSPEECH)},
year = {2022}
}
Please CITE our paper whenever the pre-trained models or the system are used to help produce published results or incorporated into other software.
For further information or requests, please go to VinAI Translate's homepage!
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