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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1157aac111ffdd3362782bdde4e9362817aee21463572c50d18091918eaea3a
- Size of remote file:
- 346 kB
- SHA256:
- cb59d4b84ee216aa04e66506d842de11cd0b22ef6769e85617d773beebc1728e
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