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 # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="VietAI/vit5-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VietAI/vit5-base") model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/vit5-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## Citation
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## Citation
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@misc{https://doi.org/10.48550/arxiv.2205.06457,
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doi = {10.48550/ARXIV.2205.06457},
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author = {Phan, Long and Tran, Hieu and Nguyen, Hieu and Trinh, Trieu H.},
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title = {ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation},
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publisher = {arXiv},
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year = {2022},
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}
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```
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