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:
- 4282947fd244d016858a7ed4443b21450746a1dacde9f2e9b0a671797d17e25f
- Size of remote file:
- 438 MB
- SHA256:
- 9d4cd64e84314eef9e3c05ea1d2e738c391c08fdef96a7efa85d8552181e4e2d
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