Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm 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-gm 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-gm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f99f0a935b7ca329d55fc6197b4273dab45003507df3a1e5f766ccb156c3eb71
- Size of remote file:
- 438 MB
- SHA256:
- 9f3f57497abefee45cf9e94e6f1522571db82c76d8ed62a6b3708a6821526e41
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