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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload ONNX weights (#2)
Verified signature- [Awaiting approval] Upload ONNX weights (e6e288dbd900f87a1e11504818024d865e57e04d)9dab549
-
Upload tiny models for DebertaV2Model
211df4b
-
Upload tiny models for DebertaV2Model
1898912 -
Upload tiny models for DebertaV2Model
2313b11
-
Upload tiny models for DebertaV2Model
a1945cc -
initial commit
7e4c988