Instructions to use wisnu001binus/hate_speech_detection_ALBERTbase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wisnu001binus/hate_speech_detection_ALBERTbase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wisnu001binus/hate_speech_detection_ALBERTbase")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wisnu001binus/hate_speech_detection_ALBERTbase") model = AutoModelForSequenceClassification.from_pretrained("wisnu001binus/hate_speech_detection_ALBERTbase") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69e26290ed2b853d69901cda2e156cc919707a22126414676ec710932d01c58e
- Size of remote file:
- 46.7 MB
- SHA256:
- 12af9ab2ca1b55e8f0112a4d42632cbd8cdd9ff345ca6d5f2417170e80517ff1
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