Instructions to use terzimert/bert-finetuned-ner-balancedData_v3.01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use terzimert/bert-finetuned-ner-balancedData_v3.01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="terzimert/bert-finetuned-ner-balancedData_v3.01")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("terzimert/bert-finetuned-ner-balancedData_v3.01") model = AutoModelForTokenClassification.from_pretrained("terzimert/bert-finetuned-ner-balancedData_v3.01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2691c54ff3c093579e693601509caae9d1816eec414e2f5171e14ad509a8d07
- Size of remote file:
- 3.58 kB
- SHA256:
- 9eeb0109ea5bb5973e5ae468d347a6af115fca437fc4b5d1b5a776c1c1187e80
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