Token Classification
Transformers
Safetensors
deberta-v2
pii-detection
named-entity-recognition
deberta
piibench
Instructions to use Pritesh-2711/piibench-deberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pritesh-2711/piibench-deberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Pritesh-2711/piibench-deberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Pritesh-2711/piibench-deberta-base") model = AutoModelForTokenClassification.from_pretrained("Pritesh-2711/piibench-deberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Pritesh-2711/piibench-deberta-base: direct link, hf CLI and curl.
- Browser
- Download file 8.33 MB
-
https://huggingface.co/Pritesh-2711/piibench-deberta-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://Pritesh-2711/piibench-deberta-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Pritesh-2711/piibench-deberta-base/resolve/main/tokenizer.json
8.33 MB
File too large to display, you can check the raw version instead.