Instructions to use microsoft/deberta-v3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-v3-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/deberta-v3-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/deberta-v3-large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.generator.bin from microsoft/deberta-v3-large: direct link, hf CLI and curl.
- Browser
- Download file 571 MB
-
https://huggingface.co/microsoft/deberta-v3-large/resolve/main/pytorch_model.generator.bin
- Command line
-
hf download hf://microsoft/deberta-v3-large/pytorch_model.generator.bin
-
curl -L -o pytorch_model.generator.bin https://huggingface.co/microsoft/deberta-v3-large/resolve/main/pytorch_model.generator.bin
571 MB
- Xet hash:
- a8a25ea38593ab46e2b41065afe9cae3ea60392c31baca436a055ab2dcc5115a
- Size of remote file:
- 571 MB
- SHA256:
- ff85455c562822ea7001f810d026a68da8a24ffdae5a095081dfe7e84e27989d
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