Instructions to use vadis/xscitldr_de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vadis/xscitldr_de with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vadis/xscitldr_de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5c5956d6dbf2b4a19d9db7e023446fc679a80a54ce9de53a4b9d32e242bbfbd4
- Size of remote file:
- 2.44 GB
- SHA256:
- bccd701a25e0a88bd127f44252cd8f0b3f5aad881aeda5e8efc73c583d95127f
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