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 bundle/libonnxruntime.dylib from DataFog/pii-en-65m: direct link, hf CLI and curl.
- Browser
- Download file 33.2 MB
-
https://huggingface.co/DataFog/pii-en-65m/resolve/main/bundle/libonnxruntime.dylib
- Command line
-
hf download hf://DataFog/pii-en-65m/bundle/libonnxruntime.dylib
-
curl -L -o libonnxruntime.dylib https://huggingface.co/DataFog/pii-en-65m/resolve/main/bundle/libonnxruntime.dylib
33.2 MB
- Xet hash:
- 4a750040e3b26e64d49eb33bd1f02447469edd142f4d512cc55a93f3fc5ce5b5
- Size of remote file:
- 33.2 MB
- SHA256:
- b46713ea6a25a5227541c21001f6422c1ccdeaecc369aa026a61b752520325c3
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