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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c94c97a8d9d3b6976713bcaf252d43f3e5c0fe3f02b07c50053264dffdac00f
- Size of remote file:
- 438 MB
- SHA256:
- 4e91d84eec4f4ee16306555b3a6b2b4d6fc2bdbdb4fd1f4a594d6ab25937c7df
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