Instructions to use warrior1127/hate_roberta_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use warrior1127/hate_roberta_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="warrior1127/hate_roberta_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("warrior1127/hate_roberta_model") model = AutoModelForSequenceClassification.from_pretrained("warrior1127/hate_roberta_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8df42326de4fa14a14e2a961daaf9fc10e0d93303acce3455ed87b4e36f9b242
- Size of remote file:
- 499 MB
- SHA256:
- 0e27c4ed0157f154bfbf30e2ba85075af574ab0db611fd9be9045870fc155867
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