Instructions to use jeniakim/hedgehog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeniakim/hedgehog with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jeniakim/hedgehog")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jeniakim/hedgehog") model = AutoModelForTokenClassification.from_pretrained("jeniakim/hedgehog") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7470a6285487499b25b37fea4ba5d36187376f5f656c941ad3204718449e9bf4
- Size of remote file:
- 2.99 kB
- SHA256:
- e399dba7a07293bdfe8bb8e90b13ee2d15b7ae606a2d6a574ce58a246aa4993d
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