Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm_revised 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_revised 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_revised")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm_revised") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm_revised") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc0a56691378b8192add2c0e24ec0b793d38306423fc70e4d9bcd0ec8ef89752
- Size of remote file:
- 438 MB
- SHA256:
- 8f799cfa5cb8862fd7128c02ee09579579eb76328d73e515c2e972296cdfd17a
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