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:
- 21f6917d780ff76e4402992d7ced81e3438f397d6b00d582f6cca7311508fe4f
- Size of remote file:
- 892 MB
- SHA256:
- deba9f8a1250a21381d091ceef30872da93f6b55a4ed6098eea441e088dc0d86
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