Instructions to use ksaml/bert-finetuned-ner-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ksaml/bert-finetuned-ner-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ksaml/bert-finetuned-ner-test")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ksaml/bert-finetuned-ner-test") model = AutoModelForTokenClassification.from_pretrained("ksaml/bert-finetuned-ner-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ee37e25fd837604b9ab4d20e88fedd9fd50a0b42ab7af8a2951473764f24e8b
- Size of remote file:
- 431 MB
- SHA256:
- 05854a9d1df75edb67fb4e61375e06dbe70b0f22b5700d86adf4f4cb3797c837
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.