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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03d762ffd7777ef94e0c5ea34af0e333f1b93bfe773396dc12eb02a6af75d708
- Size of remote file:
- 438 MB
- SHA256:
- 3cd70fed70c4188566488b50fd46aa9cbf416411928cdec9366b7945e0097294
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