Instructions to use dicta-il/dictabert-large-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dicta-il/dictabert-large-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dicta-il/dictabert-large-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dicta-il/dictabert-large-ner") model = AutoModelForTokenClassification.from_pretrained("dicta-il/dictabert-large-ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f3f2f134e7c4813c1d7037591e5cf063a0986fd34a5cf2dff7d296de75c4bd9
- Size of remote file:
- 1.74 GB
- SHA256:
- d96a273e636d9fade2fdcfe0d25aaa15491bf63926d8aef31b49705d79af790c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.