Instructions to use devagonal/t5-base-squad-qag-b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devagonal/t5-base-squad-qag-b with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("devagonal/t5-base-squad-qag-b") model = AutoModelForSeq2SeqLM.from_pretrained("devagonal/t5-base-squad-qag-b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 823e22ba04509277fdebd3688a37f5f75ef2adcf0ef2cd80c9c17fe805dd4b14
- Size of remote file:
- 892 MB
- SHA256:
- 2db9af94c696b6d069927c308921bda3caf0230f3c7ff123e0941db66e9b5705
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.