Instructions to use Falconsai/offensive_speech_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/offensive_speech_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Falconsai/offensive_speech_detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Falconsai/offensive_speech_detection") model = AutoModelForSequenceClassification.from_pretrained("Falconsai/offensive_speech_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eba1cc8fd92c2fcd4d9e8b1abca959dedfd170e9a8648e625090aebacfb0e48a
- Size of remote file:
- 536 MB
- SHA256:
- b899111ea3377e5da91f3d3a7b9a5469fe38a5d32f5d5de7ba78be8d9d05dd06
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