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:
- c805e4955f7473a4b3983f61061acf10885fd4a0e2bb9a4a98664c10c7421139
- Size of remote file:
- 6.69 MB
- SHA256:
- 7cf9858bb50a38c242f4a9ec2cdb494a95b02bfc227d03adb541f0fad2840b3f
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