Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rne 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-rne 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-rne")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rne") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rne") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3f314066e3ef39b33747d312a896f2aff581551a11c5c5dc9378833c6aa7c1b
- Size of remote file:
- 438 MB
- SHA256:
- 6c99bbe56f009ff9e1bd7a31026ebd8c0c33c717f1eb9e3c98bf99ba5e767223
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