Instructions to use liamliang/hate_speech_content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liamliang/hate_speech_content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="liamliang/hate_speech_content")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("liamliang/hate_speech_content") model = AutoModelForSequenceClassification.from_pretrained("liamliang/hate_speech_content") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3663611b3140746bc9364abe8a5e259dc40c14e35ba7e18f3ccbc52d1dcf921e
- Size of remote file:
- 438 MB
- SHA256:
- 46292d4f7b3528d82dd9ae6cd765d86e91e2771459272480e7b61814badea026
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