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:
- 357181e7c1b5c4db68bc973111524ea18a8116f15aac60a8bda392621ab401c3
- Size of remote file:
- 16.7 MB
- SHA256:
- 0753b25591f807550e93bb1c8eba4c3c2aa1e252a501857648610c1a73b1b3af
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