Instructions to use Kevin201217/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kevin201217/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Kevin201217/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Kevin201217/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("Kevin201217/bert-finetuned-ner") - Notebooks
- Google Colab
- Kaggle
bert-finetuned-ner / runs /Apr13_03-44-57_441548a08422 /events.out.tfevents.1712981803.441548a08422.2625.3
- Xet hash:
- 550ebcca1b3e09f5f10e6e446e0053f69331a2d8badcb10eb29277eaa2b323cc
- Size of remote file:
- 560 Bytes
- SHA256:
- d45e7b68317154fdce4efbbd356d6815bbeb3f0711894c5070b9a82351a86238
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.