Instructions to use andi611/bert-base-cased-ner-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andi611/bert-base-cased-ner-conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="andi611/bert-base-cased-ner-conll2003")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("andi611/bert-base-cased-ner-conll2003") model = AutoModelForTokenClassification.from_pretrained("andi611/bert-base-cased-ner-conll2003", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1695ff08a48e97c53b87659a5ba15bb2339bee3ab7eed3be294482787d6614e
- Size of remote file:
- 2.67 kB
- SHA256:
- 88100af1ec30e2f8043709d1b70d7bb9a1c842ff0d1a1ca9dbab0c346bec7e20
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