Instructions to use pulkitkumar13/dark-bert-finetuned-ner1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pulkitkumar13/dark-bert-finetuned-ner1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pulkitkumar13/dark-bert-finetuned-ner1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pulkitkumar13/dark-bert-finetuned-ner1") model = AutoModelForTokenClassification.from_pretrained("pulkitkumar13/dark-bert-finetuned-ner1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 829755693f3e2cf110a2d0987eecfd287a27577acbbd4d6af2a1723030545e26
- Size of remote file:
- 3.38 kB
- SHA256:
- 3ec119b48f9728df8e07254d3b0f27327358a4e8901d57e4390329355514c3a7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.