Instructions to use SNV/bert-ner-custom with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SNV/bert-ner-custom with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="SNV/bert-ner-custom")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("SNV/bert-ner-custom") model = AutoModelForTokenClassification.from_pretrained("SNV/bert-ner-custom", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 718d960222326ef4a285541eaf6dc449a93b8f3f13bb3fc316adc2e00d5f84c9
- Size of remote file:
- 4.6 kB
- SHA256:
- ee9907d6016f069d0531036c4603c5ab0aeea19112dd01367b00a3d2bcfce05e
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