Text Classification
Transformers
Safetensors
Turkish
bert
toxicity-detection
turkish
nlp
content-moderation
Instructions to use MeowML/ToxicBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MeowML/ToxicBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MeowML/ToxicBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MeowML/ToxicBERT") model = AutoModelForSequenceClassification.from_pretrained("MeowML/ToxicBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d4b961c06c57fae276090fc0baee49f33b922caa6a8c04073aefc2fab779d48
- Size of remote file:
- 5.71 kB
- SHA256:
- bad9e7789c84d372eb69fd51aefe63212143529e5d7d184fbdcb86b517f95c2b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.