Instructions to use hf-internal-testing/tiny-random-dpr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-dpr with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-dpr", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dba30a421900e30e609cfbca97e3633b1343e1d18e633371d64ad06637fd573c
- Size of remote file:
- 800 Bytes
- SHA256:
- 26c4d449632ea072317c16e9d4857e419b67e1b7751f81a89a87c8e75fe9484e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.