Instructions to use moonstripe/hate_speech_classification_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moonstripe/hate_speech_classification_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moonstripe/hate_speech_classification_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moonstripe/hate_speech_classification_v1") model = AutoModelForSequenceClassification.from_pretrained("moonstripe/hate_speech_classification_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 17de40da3a648227e30288b4483b61722d3d18d6d83d68c515a6da818328979a
- Size of remote file:
- 438 MB
- SHA256:
- 9c8a2bfde47990a3fe152d42457cc987177952594fbb5dd7150afc9580daebaf
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