Instructions to use NlpHUST/t5-vi-en-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NlpHUST/t5-vi-en-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NlpHUST/t5-vi-en-base") model = AutoModelForSeq2SeqLM.from_pretrained("NlpHUST/t5-vi-en-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a3b9da92abcc4265de6a2017cd90996fe3b1f850cd79f88515d6326b19bc457
- Size of remote file:
- 2.33 GB
- SHA256:
- 80d4ce2f770a14d1b64fe92d904a806d33ef5ce8990b13384e4b73c76947ffaa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.