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:
- 3644e46d70b800cb1b928b2e5ee8b2e82136de74d47dc3671eaba56ca68cf5c5
- Size of remote file:
- 438 MB
- SHA256:
- 56c4f084bfc45945294c6a64a1b6194e3424dcf763b31431d2d80bbdf776402e
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