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:
- 8407077e02a6a1689c6b3533a8f6c4deae5526d523a6b581c704b54fe239e763
- Size of remote file:
- 904 MB
- SHA256:
- 9cce6e8cccabe0a60e8334538f83332f824c17768cbdd9789b232839944bf7a7
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