Instructions to use valurank/bert-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use valurank/bert-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="valurank/bert-base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("valurank/bert-base-NER") model = AutoModelForTokenClassification.from_pretrained("valurank/bert-base-NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7df72a3273a674f146ace1c295bafcbb4c5309555c0aa1d42e4d17ed2b21ac03
- Size of remote file:
- 431 MB
- SHA256:
- 6c14f6f983a9c4e151114ca9655e5bf27e3691c52a738cab1f06c3d346ced822
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