Instructions to use hf-internal-testing/tiny-random-CanineForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CanineForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-CanineForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-CanineForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-CanineForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 901365939c1a7d4a8cdf500393509082d4afb9abb1f3825837c0ed2969f988dd
- Size of remote file:
- 4.46 MB
- SHA256:
- e62889e93d4e8b68eb1768d2663e475e2473f947d6169590f40cb57290fad04c
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