Token Classification
Transformers
ONNX
Safetensors
English
distilbert
pii
privacy
experimental
datafog
Instructions to use DataFog/pii-en-65m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataFog/pii-en-65m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DataFog/pii-en-65m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DataFog/pii-en-65m") model = AutoModelForTokenClassification.from_pretrained("DataFog/pii-en-65m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from DataFog/pii-en-65m: direct link, hf CLI and curl.
- Browser
- Download file 669 kB
-
https://huggingface.co/DataFog/pii-en-65m/resolve/4b5183087ce28e791070e84a7fd936ed7e81886a/tokenizer.json
- Command line
-
hf download hf://DataFog/pii-en-65m@4b5183087ce28e791070e84a7fd936ed7e81886a/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/DataFog/pii-en-65m/resolve/4b5183087ce28e791070e84a7fd936ed7e81886a/tokenizer.json
669 kB
File too large to display, you can check the raw version instead.