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:
- 846a69368edeee066060c29cb64e0f929c852c21fbf3977e333dc99cf6885cb4
- Size of remote file:
- 1.69 GB
- SHA256:
- 3ef03653414b24087c19b3547a2ad4c6ce3d382bb10db86cf998a02877358142
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