Instructions to use wisnu001binus/hate_speech_detection_RoBERTabase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wisnu001binus/hate_speech_detection_RoBERTabase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wisnu001binus/hate_speech_detection_RoBERTabase")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wisnu001binus/hate_speech_detection_RoBERTabase") model = AutoModelForSequenceClassification.from_pretrained("wisnu001binus/hate_speech_detection_RoBERTabase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32693fec21868375feebd29bb530d6e74b6fa28a31394bf391bb8cc9dd6c834a
- Size of remote file:
- 4.86 kB
- SHA256:
- 4846ba5740409ce7aa2ccfbfbaaeaca4a1be95f21ade289d4a14f9dfd3cecb6e
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