Instructions to use hf-tiny-model-private/tiny-random-DebertaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DebertaModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-DebertaModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DebertaModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 184a52d0d1839770a717adcc3eca69cb9a5ffd1263ec46a3b22cd26172ba90cd
- Size of remote file:
- 346 kB
- SHA256:
- eab0635057f7f99a479eb34881a541c325a2f729a2641e20ea2bc5ba6adcaa5d
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