Instructions to use hf-internal-testing/tiny-random-ModernBertForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ModernBertForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ModernBertForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ModernBertForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ModernBertForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cd94c8b12b7af662362c54baccb8d9fd887334ce112622faa66a26c22592bdc
- Size of remote file:
- 6.62 MB
- SHA256:
- 2e207e73eb585341da4d5ab764d10872336b7e1cbdf0d5bba010bead9104ddb0
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