Instructions to use almaghrabima/ner_column_bert-base-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use almaghrabima/ner_column_bert-base-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="almaghrabima/ner_column_bert-base-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("almaghrabima/ner_column_bert-base-NER") model = AutoModelForTokenClassification.from_pretrained("almaghrabima/ner_column_bert-base-NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6247720b1e3169e0ae1e08753a4d5460b01fee1f0409204a58dc01cab5822cfb
- Size of remote file:
- 431 MB
- SHA256:
- d7ab94fb2abfc6fc1cbb4a21b9246df56c92a5adf94be72639ac12dc9b5c69ba
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