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:
- 88af738e6c4a29937538a90986176bb2b4bd1d6ce4da5bc785761544bb06ba6b
- Size of remote file:
- 438 kB
- SHA256:
- 10b5eed9a0f689256bbcce967edb60bec06d2ffee65c2cd64ad148dcd18dba7c
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