Instructions to use Azma-AI/bert-base-named-entity-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azma-AI/bert-base-named-entity-extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Azma-AI/bert-base-named-entity-extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Azma-AI/bert-base-named-entity-extractor") model = AutoModelForTokenClassification.from_pretrained("Azma-AI/bert-base-named-entity-extractor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e9c1b91cdd14e557d3878234d9c82b2f98194d76d97cb9481a6ae8487648b7f
- Size of remote file:
- 434 MB
- SHA256:
- ba8245e6eefa4057300e93caef9d8360192914c271f15c8bd112283d357a954b
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