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:
- 04f3553450c1fe2a5decdf1fe3d99f5f91bb29ee8ac69f422f5bda4807c523c3
- Size of remote file:
- 3.18 kB
- SHA256:
- efcc8b100708c7e4f7081b0ec68d537dd7623ba20740027713f542dfca8c8403
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