Instructions to use hiudev/NER-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hiudev/NER-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hiudev/NER-BERT")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hiudev/NER-BERT") model = AutoModelForTokenClassification.from_pretrained("hiudev/NER-BERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e001eafda41718f6deaff125e12a38a5c35bd8b402a541c7a37e68456e60cb2b
- Size of remote file:
- 5.24 kB
- SHA256:
- 4a3d8d321f1772225c7f50336b8fc71ea253ff4bcfd456f6bf41e64c27753d7f
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