Question Answering
Transformers
PyTorch
TensorFlow
JAX
Vietnamese
t5
text2text-generation
summarization
translation
text-generation-inference
Instructions to use VietAI/envit5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VietAI/envit5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="VietAI/envit5-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("VietAI/envit5-base") model = AutoModelForSeq2SeqLM.from_pretrained("VietAI/envit5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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# EnViT5-base
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State-of-the-art pretrained Transformer-based encoder-decoder model for Vietnamese and English.
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## How to use
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For more details, do check out [our Github repo](https://github.com/vietai/mtet).
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# EnViT5-base
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State-of-the-art pretrained Transformer-based encoder-decoder model for Vietnamese and English used in [MTet's paper](https://arxiv.org/abs/2210.05610).
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## How to use
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For more details, do check out [our Github repo](https://github.com/vietai/mtet).
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