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:
- b6d40582de23e077fe3929f316c8c38ec31ad54ac9f8d85401d5b4ae3f513550
- Size of remote file:
- 6.56 MB
- SHA256:
- c070ece90a82be01a51537a1f118477390a7e8ef9ee3dda63aaae18470b5b68e
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