Instructions to use EddyGiusepe/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EddyGiusepe/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EddyGiusepe/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EddyGiusepe/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("EddyGiusepe/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e9879a15457f0fcf50cbebf6dd690b684a6732e2816c04f356d9fb1c1a03d55b
- Size of remote file:
- 431 MB
- SHA256:
- f33f4c0f105fcc788b51ed33aefe0e15bedab2838a71be5c80818e506ff1c29c
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