Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-1 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-1 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-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-1") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1c5b6ada21d3603447f6aa746cf064d651390b13e6e053f3a1549129a9ad83a
- Size of remote file:
- 438 MB
- SHA256:
- 4dc2f4326b0896ca3ad7433acdb5ad22bb45828786771c9f8820cc1eb2997a21
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