Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification 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-RobertaPreLayerNormForTokenClassification 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-RobertaPreLayerNormForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e1b378883fbb1f60c269dd8728fd62619df77a76ba05a9a396f3f292dc4c5b0
- Size of remote file:
- 369 kB
- SHA256:
- 02d22a082dd85173cab54c61c7aba631b0c858c5d578ae42baca42de5614d490
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