Instructions to use hf-internal-testing/tiny-random-DebertaV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DebertaV2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DebertaV2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6164fcb33d3071c2d9d6eea1c7480fa5d9759e1823c0e9d1cbc769d577d5739e
- Size of remote file:
- 16.6 MB
- SHA256:
- 95a2a686eab392381e54d033c71dad473d91850b2e24c2d45e9a3b3f19417370
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