Instructions to use hf-tiny-model-private/tiny-random-CanineForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-CanineForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-CanineForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-CanineForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-CanineForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d92f398f85db380906768f21e0d6b29996332afecea475d22fcee44925b3dd5
- Size of remote file:
- 4.46 MB
- SHA256:
- f8c69d288d198af8875a45a09a4f519236322ba968e098b2795cb3da3e2d46ce
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