Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-2 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-something__round-2 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-something__round-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-2") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aeee895742d9de1afb6b4fad705d93572251004b9405231d35dfbeb953939a70
- Size of remote file:
- 438 MB
- SHA256:
- fd4e2f9a3794e02b241a6b68885255c1c8adef8e3d960c8c1dcc5e1d82a7f301
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