Instructions to use peft-internal-testing/tiny-random-DebertaV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peft-internal-testing/tiny-random-DebertaV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="peft-internal-testing/tiny-random-DebertaV2Model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("peft-internal-testing/tiny-random-DebertaV2Model") model = AutoModel.from_pretrained("peft-internal-testing/tiny-random-DebertaV2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e40ced40eeb91421bd94d0cf554ad2c1fd2dd572cfd2139dc94c5dcfe20bf942
- Size of remote file:
- 16.6 MB
- SHA256:
- 0cb05c636f416a51f57ff263dca5b3ad1469b756ebc3a29f8f15455a6e3150b0
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