Instructions to use microsoft/deberta-v3-xsmall with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-v3-xsmall with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/deberta-v3-xsmall")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/deberta-v3-xsmall", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/deberta-v3-xsmall: direct link, hf CLI and curl.
- Browser
- Download file 241 MB
-
https://huggingface.co/microsoft/deberta-v3-xsmall/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/deberta-v3-xsmall/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/deberta-v3-xsmall/resolve/main/pytorch_model.bin
241 MB
- Xet hash:
- 66c54d18a131a1aa6bd10c6f9c275753b89e1561814ac28c04e80f438db62249
- Size of remote file:
- 241 MB
- SHA256:
- e96369113d0ea430d5827a651182f3079438ef1191b608a312b893ce98052c0a
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