Instructions to use summaria/qa-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use summaria/qa-t5 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("summaria/qa-t5") model = AutoModelForSeq2SeqLM.from_pretrained("summaria/qa-t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3efa9c89ffb84cae0e5f0118e177230be4f6a261db60fae168724378281529e
- Size of remote file:
- 623 Bytes
- SHA256:
- 99193fa90e0e53b03c7bf66335a0500aa5bd6fcd9e1eeaa58465964c69a086ff
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