Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification 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-RobertaPreLayerNormForTokenClassification 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-RobertaPreLayerNormForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 521b946e5de50ce119ebd42382a6fdd836179555b3f3837df66cc2c87a787a95
- Size of remote file:
- 350 kB
- SHA256:
- b54c1a65f3ce8cc1ea20ce54401df4be373bc52d8e6cee7e9a385c34a0eb7139
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