Instructions to use gaussalgo/T5-LM-Large_Canard-HotpotQA-rephrase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaussalgo/T5-LM-Large_Canard-HotpotQA-rephrase with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gaussalgo/T5-LM-Large_Canard-HotpotQA-rephrase") model = AutoModelForSeq2SeqLM.from_pretrained("gaussalgo/T5-LM-Large_Canard-HotpotQA-rephrase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 174b01c6b0b36a8f645f5426c8c79798f3ebcb8f8fd9c8e0f27afae36301d53d
- Size of remote file:
- 3.13 GB
- SHA256:
- 2b7310253183b1ae84a687eee7cc75265e9f13336f4f27a8060523402b28d879
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.