Instructions to use mpalaval/bert-ner-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/bert-ner-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/bert-ner-5")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/bert-ner-5") model = AutoModelForTokenClassification.from_pretrained("mpalaval/bert-ner-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08d8808b7e4796085bf1e64366e1a614d247a99903d22a119210cedb2656ed32
- Size of remote file:
- 431 MB
- SHA256:
- ee1eedb21762869aa1854efd2f895cf4ef1c414fb7db95026a339a8c01e421ad
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