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:
- ef59b8763a80fe17b0d17700e07733033fb84e86379cc0064d65b493f2f42e9f
- Size of remote file:
- 431 MB
- SHA256:
- df0a11db02a0be2fe4699cf9944088f411a269f046bc3f6e615293803d57bb8e
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