Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ra 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-ra 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-ra")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ra") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ra") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 224ec70875df02657caa3a5a6803bbb29b4f98fa488a66f827598d3020750e02
- Size of remote file:
- 3.39 kB
- SHA256:
- 9a4fece764527285e306b4670f990c95388351131d84233b70e3c24e00f87dcd
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