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:
- 9e7a07e7a3020c1ea22ed5c93769c55718488d165dd5179097dddf7d4b0d265c
- Size of remote file:
- 4.49 MB
- SHA256:
- 0f4c5cce1c2cdb8f3af90bc88518f3de222cabe8307d75cb1178a3989694c2cc
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