Instructions to use hf-internal-testing/tiny-random-RoFormerForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoFormerForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-RoFormerForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoFormerForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-RoFormerForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aea009924be8bb379f0e8bc3ce2d4e09941d75edbff72209044df63f93983311
- Size of remote file:
- 6.56 MB
- SHA256:
- 01b63f7acdabb183fe301892a59c67ecb6694abef049a10cb19e3fe6a76c0908
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