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") - Notebooks
- Google Colab
- Kaggle
root commited on
Commit ·
fb6f40a
1
Parent(s): 3d892d5
Add flax model
Browse files- flax_model.msgpack +3 -0
- tokenizer.json +0 -0
flax_model.msgpack
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oid sha256:ffe41b25a819e3861e62e67a381c0f2f4814a112b767e51d7afb13ede37bc9f5
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tokenizer.json
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