Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13e4415b734e367ef7970413d0d42ff54a1790fbcba3d1e13cecaaf2cab3ff0e
- Size of remote file:
- 438 MB
- SHA256:
- 2f02fb259a21ef11ac36ee308d81585ac8d58a9072a66c2ee95a8b44d2c22fe7
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