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:
- 037a6fea0cf84d6adf6d7c3febc4da8c20ce88d1ce537170c895f4f62913e830
- Size of remote file:
- 463 kB
- SHA256:
- b2a25276cfb7d5e900da1e406af5610249ced4af26f8e5d3f8af18377ec6035c
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