Token Classification
Transformers
Safetensors
Turkish
bert
ner
turkish
academic
anonymization
kvkk
berturk
tr-academic-nlp
Instructions to use hakansabunis/trakad-ner-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hakansabunis/trakad-ner-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hakansabunis/trakad-ner-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hakansabunis/trakad-ner-v1") model = AutoModelForTokenClassification.from_pretrained("hakansabunis/trakad-ner-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59aa4863d6141d119945f5ac5cf99abec7eac2c1441e507089d7b5550d1f5c33
- Size of remote file:
- 4.86 kB
- SHA256:
- ceec5716379b9f67d476896281cddf8673154f5dfdb55a5efed959d7bd253e02
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