Text Classification
Transformers
Safetensors
Turkish
bert
bseby
bddk
banking
data-classification
dlp
kvkk
pii
privacy
multi-label
turkish
text-embeddings-inference
Instructions to use halilneed/turkish-bseby-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halilneed/turkish-bseby-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="halilneed/turkish-bseby-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("halilneed/turkish-bseby-classifier") model = AutoModelForSequenceClassification.from_pretrained("halilneed/turkish-bseby-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download thresholds.json from halilneed/turkish-bseby-classifier: direct link, hf CLI and curl.
- Browser
- Download file 121 Bytes
-
https://huggingface.co/halilneed/turkish-bseby-classifier/resolve/main/thresholds.json
- Command line
-
hf download hf://halilneed/turkish-bseby-classifier/thresholds.json
-
curl -L -o thresholds.json https://huggingface.co/halilneed/turkish-bseby-classifier/resolve/main/thresholds.json
121 Bytes
| { | |
| "kisisel_veri": 0.5, | |
| "ozel_nitelikli": 0.15, | |
| "hassas_veri": 0.2, | |
| "musteri_sirri": 0.5, | |
| "banka_sirri": 0.15 | |
| } |