Instructions to use yysung53/dpr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yysung53/dpr with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yysung53/dpr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6eeeb5ab93fdc349c10e98e99f88d409a5b8082a927f2d030408c714fe7b1147
- Size of remote file:
- 438 MB
- SHA256:
- 9075e1dee14bce7f825496635e8f687a52fff27bb7c825061df0a742ca65983f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.