Instructions to use ydshieh/tiny-random-DebertaForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ydshieh/tiny-random-DebertaForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("ydshieh/tiny-random-DebertaForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-DebertaForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 361 kB
-
https://huggingface.co/ydshieh/tiny-random-DebertaForTokenClassification/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaForTokenClassification@refs/pr/2/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaForTokenClassification/resolve/refs%2Fpr%2F2/pytorch_model.bin
361 kB
- Xet hash:
- 982388b41a3d5bbc18ec512661801424835cf89d96a5bad9dd1c3d85da5e8fc4
- Size of remote file:
- 361 kB
- SHA256:
- 1965952731f8cb6ed8498e678e23355273f0fb114978b3c78f9ab7517a8e0404
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