Instructions to use hf-internal-testing/tiny-random-DebertaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DebertaModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DebertaModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70b433f4e526398034b15a958acfb04303dc6bbd385001ae26907b55624c3927
- Size of remote file:
- 360 kB
- SHA256:
- c747ba3a15895a7c123706982ea88bf68fffa0a8da27e1490b92083e8def89da
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