Instructions to use mpalaval/bert-ner-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/bert-ner-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/bert-ner-2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/bert-ner-2") model = AutoModelForTokenClassification.from_pretrained("mpalaval/bert-ner-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78e76029854ebf004210d786d9f43613603adf4b0c147524ebc14509e89d766d
- Size of remote file:
- 4.54 kB
- SHA256:
- 401c8030bd27c184ded81faabb13a2b5c60952d5143f9a4440ba2b55256a80bc
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