Instructions to use ydshieh/tiny-random-DebertaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ydshieh/tiny-random-DebertaModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaModel") model = AutoModel.from_pretrained("ydshieh/tiny-random-DebertaModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-DebertaModel: direct link, hf CLI and curl.
- Browser
- Download file 359 kB
-
https://huggingface.co/ydshieh/tiny-random-DebertaModel/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaModel@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaModel/resolve/refs%2Fpr%2F2/pytorch_model.bin
359 kB
- Xet hash:
- 92ae3c94448c4e74a617df851a5b2f97db07af31a2a571a516869d5a2a4f0fee
- Size of remote file:
- 359 kB
- SHA256:
- 71004c651a9eb3b50d633afdf3a14ce4df7698bd7595a56f6f8a4a677a6f9d02
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