Instructions to use xnohat/t5-vietnamese-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xnohat/t5-vietnamese-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("xnohat/t5-vietnamese-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("xnohat/t5-vietnamese-summarization") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
https://huggingface.co/pengold/t5-vietnamese-summarization with ONNX weights to be compatible with Transformers.js.
Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).
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