Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda 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-eda 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-eda")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 981a6f383a3980724b064ae45d4c5e0c3fb3b8f0c5d9a53d1cc9d674242a6fde
- Size of remote file:
- 438 MB
- SHA256:
- b440ec354ec11cee30a1622f9a1bf4ad0c303c8bd6658e03f8cdc7ccff592f1f
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