Instructions to use Prience91/ner_model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Prience91/ner_model_output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Prience91/ner_model_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Prience91/ner_model_output") model = AutoModelForTokenClassification.from_pretrained("Prience91/ner_model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 299 Bytes
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"pad_token": "[PAD]",
"sep_token": "[SEP]",
"tokenizer_class": "TokenizersBackend",
"unk_token": "[UNK]"
}
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