Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-2 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-something__round-2 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-something__round-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-2") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 90f9413ab24c053c0e12ca84bf21fb5ab6b108da5e2165eae4bab7faf03fce4c
- Size of remote file:
- 438 MB
- SHA256:
- e2b7ff42775cc213974fbfc96e1037355c9d0f42d01d7c56b1e2c88512a84ce5
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