Instructions to use huggingface-course/bert-finetuned-ner-accelerate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingface-course/bert-finetuned-ner-accelerate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="huggingface-course/bert-finetuned-ner-accelerate")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("huggingface-course/bert-finetuned-ner-accelerate") model = AutoModelForTokenClassification.from_pretrained("huggingface-course/bert-finetuned-ner-accelerate") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- def3ffbc968df94ea00ffdce9e0d8c16057b14fef966ef75e36ad601c850a21f
- Size of remote file:
- 431 MB
- SHA256:
- 336e1566150fd3a4cf3d524dbd4fd3f004e8b0bd5c2d038226bb173512cc2e42
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