Text Classification
Transformers
Safetensors
Turkish
English
bert
kvkk
verbis
gdpr
pii
privacy
data-classification
multi-label
turkish
pii-detection
personal-data
sensitive-data
data-masking
Eval Results (legacy)
text-embeddings-inference
Instructions to use halilneed/turkish-kvkk-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halilneed/turkish-kvkk-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="halilneed/turkish-kvkk-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("halilneed/turkish-kvkk-classifier") model = AutoModelForSequenceClassification.from_pretrained("halilneed/turkish-kvkk-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download thresholds.json from halilneed/turkish-kvkk-classifier: direct link, hf CLI and curl.
- Browser
- Download file 554 Bytes
-
https://huggingface.co/halilneed/turkish-kvkk-classifier/resolve/main/thresholds.json
- Command line
-
hf download hf://halilneed/turkish-kvkk-classifier/thresholds.json
-
curl -L -o thresholds.json https://huggingface.co/halilneed/turkish-kvkk-classifier/resolve/main/thresholds.json
554 Bytes
| { | |
| "kimlik": 0.55, | |
| "iletisim": 0.8, | |
| "lokasyon": 0.3, | |
| "ozluk": 0.2, | |
| "hukuki_islem": 0.75, | |
| "musteri_islem": 0.35, | |
| "fiziksel_mekan_guvenligi": 0.15, | |
| "islem_guvenligi": 0.5, | |
| "risk_yonetimi": 0.25, | |
| "finans": 0.4, | |
| "mesleki_deneyim": 0.15, | |
| "pazarlama": 0.1, | |
| "gorsel_isitsel": 0.35, | |
| "arac": 0.5, | |
| "saglik": 0.35, | |
| "biyometrik": 0.2, | |
| "genetik": 0.1, | |
| "cinsel_hayat": 0.45, | |
| "ceza_mahkumiyeti": 0.3, | |
| "din_felsefi_inanc": 0.1, | |
| "siyasi_dusunce": 0.2, | |
| "irk_etnik": 0.35, | |
| "dernek_vakif_sendika": 0.15, | |
| "kilik_kiyafet": 0.1 | |
| } |