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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("VietAI/envit5-base") model = AutoModelForMultimodalLM.from_pretrained("VietAI/envit5-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c9a4619271698ebf919b08d9ea29b567b05dfec02dc1c88ff3f84c414af1d48
- Size of remote file:
- 1.1 GB
- SHA256:
- ffe41b25a819e3861e62e67a381c0f2f4814a112b767e51d7afb13ede37bc9f5
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