Question Answering
Transformers
PyTorch
TensorFlow
JAX
Vietnamese
t5
text2text-generation
summarization
translation
text-generation-inference
Instructions to use VietAI/vit5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VietAI/vit5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VietAI/vit5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VietAI/vit5-base") model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/vit5-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8a19d7d9a2a7a0bc77a3be92df53aeafcdf421706dd5763cf4f781d042a1a87
- Size of remote file:
- 904 MB
- SHA256:
- 6e666460219d3495e6437ac09061425ccf896532c92ec00cd3e6130cc94f3f44
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