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:
- c9993859c641290096e1cb58596c0ab6ddffb2f8df456f708535a18b60e4e11f
- Size of remote file:
- 268 MB
- SHA256:
- 39d37f832bcc5130375bd55ff03fcdc605dd1b107daf02d94f9ab70bd5a03870
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