Token Classification
Transformers
Safetensors
xlm-roberta
ner
pii
pii-detection
redaction
privacy
dpdp
aadhaar
pan
upi
gstin
indic
indian-languages
hinglish
code-mixed
hindi
bengali
tamil
telugu
marathi
gujarati
kannada
malayalam
punjabi
urdu
odia
named-entity-recognition
personal-data
data-masking
anonymization
de-identification
data-privacy
voter-id
ifsc
india
Eval Results (legacy)
Instructions to use arunp0/chitragupta-pii-indic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arunp0/chitragupta-pii-indic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="arunp0/chitragupta-pii-indic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("arunp0/chitragupta-pii-indic") model = AutoModelForTokenClassification.from_pretrained("arunp0/chitragupta-pii-indic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/cover.png from arunp0/chitragupta-pii-indic: direct link, hf CLI and curl.
- Browser
- Download file 94.2 kB
-
https://huggingface.co/arunp0/chitragupta-pii-indic/resolve/main/assets/cover.png
- Command line
-
hf download hf://arunp0/chitragupta-pii-indic/assets/cover.png
-
curl -L -o cover.png https://huggingface.co/arunp0/chitragupta-pii-indic/resolve/main/assets/cover.png
94.2 kB
