Instructions to use deepvk/deberta-v1-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepvk/deberta-v1-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="deepvk/deberta-v1-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("deepvk/deberta-v1-base") model = AutoModel.from_pretrained("deepvk/deberta-v1-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ac7217fbc338a531e217100b86e3e4ba432f656634c399eb98055074f90b839
- Size of remote file:
- 496 MB
- SHA256:
- 34ee881571c9a8d47119bdaddc16e5ae8f9f101a1e6da58cded7e05e28905596
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