Question Answering
Transformers
PyTorch
TensorFlow
JAX
Vietnamese
t5
text2text-generation
summarization
translation
text-generation-inference
Instructions to use VietAI/vit5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VietAI/vit5-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VietAI/vit5-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VietAI/vit5-large") model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/vit5-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2df9c840189576eb6759cf2eacd6d8c5a97fbb5982822a9469fa0f2b6625a352
- Size of remote file:
- 3.17 GB
- SHA256:
- 0c2dab620820db1b77933a458bdb40b5f3715b50a4413664b42f6e73dbb41ce0
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