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:
- 62008aa6c3c5943229f79dc05b93f5151c8a070bdd9c92282167274531020d75
- Size of remote file:
- 6.58 MB
- SHA256:
- 1ac488826770ae4945ce1900378c30ce8e02f913133eb1b72b18a9e7f572b212
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