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.bin from microsoft/deberta-v3-large: direct link, hf CLI and curl.
- Browser
- Download file 874 MB
-
https://huggingface.co/microsoft/deberta-v3-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/deberta-v3-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/deberta-v3-large/resolve/main/pytorch_model.bin
874 MB
- Xet hash:
- 8bf604e0344f158831a639481826026f84828a0f38efeab21e43b6ed6e185a03
- Size of remote file:
- 874 MB
- SHA256:
- dd5b5d93e2db101aaf281df0ea1216c07ad73620ff59c5b42dccac4bf2eef5b5
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