Instructions to use madanagrawal/token_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madanagrawal/token_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="madanagrawal/token_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("madanagrawal/token_classifier") model = AutoModelForTokenClassification.from_pretrained("madanagrawal/token_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0323ead60867d67fd89d161575059a0669908c6ef93dfdc2f18577ddbb7509b2
- Size of remote file:
- 4.73 kB
- SHA256:
- b11995f2cb758357d289ddc69a595bf49edaa820b3d82552818abb2fd2dee102
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.