Instructions to use khhuang/zerofec-qa2claim-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khhuang/zerofec-qa2claim-t5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("khhuang/zerofec-qa2claim-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("khhuang/zerofec-qa2claim-t5-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f3981796dd9eb196a15d60432cac095ed7cef5ccb1be16534cfa5262741808f
- Size of remote file:
- 892 MB
- SHA256:
- 1e1b32cbd46475f07bb313ae90eb471fff483143a2de75a55d2e507296476a10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.