Text Classification
Transformers
PyTorch
Turkish
bert
text
news-category-classification
text-embeddings-inference
Instructions to use yavuzkomecoglu/news-category-classification-tr-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yavuzkomecoglu/news-category-classification-tr-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yavuzkomecoglu/news-category-classification-tr-test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yavuzkomecoglu/news-category-classification-tr-test") model = AutoModelForSequenceClassification.from_pretrained("yavuzkomecoglu/news-category-classification-tr-test") - Notebooks
- Google Colab
- Kaggle
INTERPRESS TURKISH NEWS CATEGORY CLASSIFICATION MODEL - TEST - v0.1
LABELS = { 0: 'spor', 1: 'is_ve_finans', 2: 'lifestyle', 3: 'eglence', 4: 'seyahat', 5: 'egitim', 6: 'bilim', 7: 'teknoloji', 8: 'kultur_sanat', 9: 'otomotiv', 10: 'politika', 11: 'endustri', 12: 'moda', 13: 'yemek' }
ACC = 0.9128, F1 = 0.7142, PRECISION = 0.7355, RECALL = 0.06996
- Downloads last month
- 7