Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ri 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-ri 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-ri")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ri") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ri") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d5d3cbf2d750bc885455747b5f94a61c18bcf0d66e99183a6d0187ce7626914
- Size of remote file:
- 438 MB
- SHA256:
- a3e991d64f5e0093a0ed42e3c83b9b32c7614e40ec3436023e8a9b09f27e3aa8
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