Instructions to use savasy/bert-turkish-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use savasy/bert-turkish-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="savasy/bert-turkish-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("savasy/bert-turkish-text-classification") model = AutoModelForSequenceClassification.from_pretrained("savasy/bert-turkish-text-classification") - Notebooks
- Google Colab
- Kaggle
ConfusioninLang
#2
by Yucaib - opened
I tried that sentence "dünyada sağlık çok iyi yerelere geliyor " but it answerd as [{'label': 'health', 'score': 0.9494585990905762}], actually it works just fine but in your description they were turkish so I wanted to ask about it. Thanks for your efforts btw. I couldn't understand why this happend btw
Hi Yucaib,
It is a text classification model. And it classifies text input, which is about health, so the model makes it (%95 health) correctly!
I may not understand your Q, sorry for the late reply!