Instructions to use hungphongtrn/vi_en_vinai-translate-vi2en-v2_conv_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hungphongtrn/vi_en_vinai-translate-vi2en-v2_conv_train with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("hungphongtrn/vi_en_vinai-translate-vi2en-v2_conv_train") model = AutoModelForMultimodalLM.from_pretrained("hungphongtrn/vi_en_vinai-translate-vi2en-v2_conv_train") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62b0f88471ace75386d93d07dfe00ddf520c8588a22bbd7842ab569a2a919519
- Size of remote file:
- 1.41 MB
- SHA256:
- cdbd2277deee13a943b702c0131ea9034d00c2288f332ee0c5fea520b07ea936
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