Instructions to use dany0407/token_classification_NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dany0407/token_classification_NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="dany0407/token_classification_NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dany0407/token_classification_NER") model = AutoModelForTokenClassification.from_pretrained("dany0407/token_classification_NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71c6e00b31a43b9409136f8a2850fb469548d69205b9ebc68553ecd7d478151d
- Size of remote file:
- 266 MB
- SHA256:
- d2eca9f06142d01746652876af345289b0b6687976a645d4dcf33688579051f7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.