Instructions to use textminr/ner-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textminr/ner-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="textminr/ner-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("textminr/ner-bert") model = AutoModelForTokenClassification.from_pretrained("textminr/ner-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e41fccd7a7bee357426133b2af780ee0996ce9636f8844dc3aa43eea0ec2ef2c
- Size of remote file:
- 4.73 kB
- SHA256:
- c1d5e938cbcbb03ee4bb87ea11a02d28da97ea40c34a53f6702451049e93d243
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