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:
- 7c3b6d92a2ef7e2e91be61cf71012726e2ad9344d6b1a41848dcc8f4a3197019
- Size of remote file:
- 438 MB
- SHA256:
- a8eb25b6ebea2ff8a6a1265e5262d08ac78400664db7304c75cd46f11ff706ec
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