Instructions to use hf-internal-testing/tiny-random-RobertaPreLayerNormForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RobertaPreLayerNormForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-RobertaPreLayerNormForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-RobertaPreLayerNormForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a0b05fa1cc412374e2002d9db99607056b75a41103416e0b51b75b6991925e7
- Size of remote file:
- 350 kB
- SHA256:
- 27682fde2b1760ab4c1abc089a06bdeecb5d8f2176335e11e93067b4af51efc8
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