Instructions to use readerbench/RoBERT-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use readerbench/RoBERT-base with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("readerbench/RoBERT-base", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78454748edcf5f54dca079cf7c46b183cfdea8ca9cb823716273c243b7530a8a
- Size of remote file:
- 463 MB
- SHA256:
- 508a139d8afc93ad99c4e853ef1522496f9d365705b6d1c0b430f3b37e3e8ca1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.