Instructions to use KPF/KPF-bert-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KPF/KPF-bert-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="KPF/KPF-bert-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("KPF/KPF-bert-ner") model = AutoModelForTokenClassification.from_pretrained("KPF/KPF-bert-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 116e4b739ee586f015678851e54b6d1c40c93a991df09b17fae770fcb0598d73
- Size of remote file:
- 455 MB
- SHA256:
- eb1aaa759888b28d22d4075ea026eaa6401f22145fad60b2495ce0369a55024e
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