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%2F5/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaForTokenClassification@refs/pr/5/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaForTokenClassification/resolve/refs%2Fpr%2F5/pytorch_model.bin
361 kB
- Xet hash:
- 509751446fca992b882391a3921403d91c16cdd3f67fa19c2d3945ddd3a836b4
- Size of remote file:
- 361 kB
- SHA256:
- 5058de548da2f30ad2c5496acc7487119d0ea23da09c3e229a12cc2430c40d42
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