Instructions to use hf-tiny-model-private/tiny-random-RoFormerForTokenClassification 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-RoFormerForTokenClassification 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-RoFormerForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b07475345468e00e5b44486ce784ebb9f412cae43de8650a601831d2ca4fc4e8
- Size of remote file:
- 6.68 MB
- SHA256:
- baed8b28ce132c70390575add2843491d89b980b994e998ea56604fb63739624
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