Instructions to use ydshieh/tiny-random-DebertaV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ydshieh/tiny-random-DebertaV2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaV2Model") model = AutoModel.from_pretrained("ydshieh/tiny-random-DebertaV2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a77c96e01535ff591685ebf11f18d5c9e08da832e0dd6c4f7b592783e04143b3
- Size of remote file:
- 365 kB
- SHA256:
- c3b17e157b9afb7ead4707ab8083d6dc62a37734afe527bdbacc85f7af47ac79
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