Instructions to use microsoft/deberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/deberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/deberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download rust_model.ot from microsoft/deberta-base: direct link, hf CLI and curl.
- Browser
- Download file 559 MB
-
https://huggingface.co/microsoft/deberta-base/resolve/main/rust_model.ot
- Command line
-
hf download hf://microsoft/deberta-base/rust_model.ot
-
curl -L -o rust_model.ot https://huggingface.co/microsoft/deberta-base/resolve/main/rust_model.ot
559 MB
- Xet hash:
- 0119b8255a976f515add308362a41354eb246db45ecbacdd51188fa500bbc01a
- Size of remote file:
- 559 MB
- SHA256:
- 42a8937bf8d3d98be44be18d92c0fafdebcddf839c8be2d72e18ec1b408b1e3c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.