Instructions to use mpalaval/bert-ner-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mpalaval/bert-ner-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mpalaval/bert-ner-4")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("mpalaval/bert-ner-4") model = AutoModelForTokenClassification.from_pretrained("mpalaval/bert-ner-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5db8452529438e2aac37d670d507223734daf2cfaff5ac938dc2bcd5dd51aa13
- Size of remote file:
- 431 MB
- SHA256:
- 18c50ba1471494c60d8c56d72888bf9aca3f675fe516d8aca8d039814d3a4273
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