| # Hate Speech Classification v1 | |
| ## Overview | |
| The "Hate Speech Classification v1" is a model designed to classify hate speech in text data. It has been trained on the "ucberkeley-dlab/measuring-hate-speech" dataset to effectively identify instances of hate speech. | |
| ## Usage | |
| ### Installation | |
| To use the "Hate Speech Classification v1," you'll need to have the Hugging Face Transformers library installed. You can install it using pip: | |
| ```bash | |
| pip install transformers | |
| ``` | |
| ### Usage | |
| You can load and use the "Hate Speech Classification v1" in your Python code by following these steps: | |
| ```python | |
| from transformers import pipeline | |
| model = pipeline(model="moonstripe/hate_speech_classification_v1") | |
| model("Hello world") | |
| # Interpret the predictions to determine hate speech classification | |
| # ... | |
| # Clean up resources as needed | |
| `````` |