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%2F5/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaModel@refs/pr/5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaModel/resolve/refs%2Fpr%2F5/pytorch_model.bin
359 kB
- Xet hash:
- 60d94904225e9b166a220a304a74e57ca9269df9a1c3491b8d36ae6e37153713
- Size of remote file:
- 359 kB
- SHA256:
- 57e4f6d924b33d249c8b9ca3c8521946b7bc86a2a89d922bec9823b140520e99
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