Instructions to use rollerhafeezh/xlm-roberta-base-ner-augmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rollerhafeezh/xlm-roberta-base-ner-augmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rollerhafeezh/xlm-roberta-base-ner-augmentation")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rollerhafeezh/xlm-roberta-base-ner-augmentation") model = AutoModelForTokenClassification.from_pretrained("rollerhafeezh/xlm-roberta-base-ner-augmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8db672676f02cda7a7855c1866ed1feffa438813f777f149a8f1ff977c07fcd6
- Size of remote file:
- 17.1 MB
- SHA256:
- 19232daba569c004c5fbe45f373ccaf2ee505055da00969f78a99e5754db8f25
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