Instructions to use NlpHUST/t5-vi-en-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NlpHUST/t5-vi-en-small with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NlpHUST/t5-vi-en-small") model = AutoModelForSeq2SeqLM.from_pretrained("NlpHUST/t5-vi-en-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcb6fc43a2721aee303d35aca18b06e70f39440684b1d56d90987b75f42dcf3a
- Size of remote file:
- 1.2 GB
- SHA256:
- e9333806fa8223e1aa1d20e2d9a5996ad2b695877db8775f5a815ace323bcde3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.