Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ri 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-ri 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-ri")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ri") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-ri") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b232e7c6b057cfe09159b1eadd2b9d8bc7f83dda86baec1895b6d1f0439f9fa
- Size of remote file:
- 3.39 kB
- SHA256:
- bd2873aef2c0f8c050623f3a558655f9747c8934a151a4a4a3ad712ce9a6317b
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