Instructions to use hf-tiny-model-private/tiny-random-RobertaForTokenClassification 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-RobertaForTokenClassification 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-RobertaForTokenClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4f0912acd72327bf725aca01301f5d588b0dd8ebfdaf29fa44ac40c7705f4e1
- Size of remote file:
- 462 kB
- SHA256:
- 762ac7861c8f6a3068aecb04bc9bb1c8d61392af1015b882a9f915736cc2ce1a
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