Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all 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-all 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-all")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4747c745648776f4c896fa2a277d751992327daaa2616d06b8458f48b1dfc31b
- Size of remote file:
- 438 MB
- SHA256:
- 92e3f7cbba2bcf32da26bc87e13a028364f9745477c7be1b0605e849cf0896f7
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