Instructions to use Repv1111/En-Vi-Neural-Machine-Translation-using-Transformers-based-vebe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Repv1111/En-Vi-Neural-Machine-Translation-using-Transformers-based-vebe with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Repv1111/En-Vi-Neural-Machine-Translation-using-Transformers-based-vebe", dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 377cc315a36a47b060fedf1262609ec19614e3376ef7e7f61e878114d8c9f26e
- Size of remote file:
- 113 MB
- SHA256:
- 22c46640ca5ab4011df9d37f3df3d33eed94af1dbb513948ffdb36df23297f62
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