Instructions to use PursuitOfDataScience/bert-base-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PursuitOfDataScience/bert-base-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="PursuitOfDataScience/bert-base-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("PursuitOfDataScience/bert-base-ner") model = AutoModelForTokenClassification.from_pretrained("PursuitOfDataScience/bert-base-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74eb31896b49246c0fff11d401a3d533e25edd1fc7b095831f744a30a6c35c82
- Size of remote file:
- 436 MB
- SHA256:
- df6c1ce1ae614052aa3c57695ec9e62f14ae9a14f1f4e10d1dad3ce537b07fda
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