Instructions to use hemekci/off_detection_turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hemekci/off_detection_turkish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hemekci/off_detection_turkish")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hemekci/off_detection_turkish") model = AutoModelForSequenceClassification.from_pretrained("hemekci/off_detection_turkish") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9747c00f677b4c5d28ab127d930e8601eeac06b7d2701d22f64b8674a7e2e33
- Size of remote file:
- 737 MB
- SHA256:
- 245508596123b1b0f5a2d5c8c25a7204ed5935e44222bf275ce8da684cfa09fb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.