Instructions to use summaria/qa-qg-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use summaria/qa-qg-t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("summaria/qa-qg-t5") model = AutoModelForSeq2SeqLM.from_pretrained("summaria/qa-qg-t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc64a240fe7fd988cf8cbb389561d03a1a6c7d89af6d3725c7de339934ff0e61
- Size of remote file:
- 2.14 MB
- SHA256:
- 897164d5959c087a7c9fdd1844d951af14782bfda43a7036320a2f03bcf75680
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