Instructions to use ShinDC/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShinDC/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ShinDC/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ShinDC/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("ShinDC/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8548532f1e124cf139d29f8b0f87e2a710fa99090687dc415b9289e83af3f2d
- Size of remote file:
- 431 MB
- SHA256:
- 9aae6ca95cda51466b9f35b62da0ea7ba9b3e73f9fa9d31f0c01d7705499f182
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.