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:
- 5931087fdd0d338d34aec8bc8020e9de9481582582edaf939922ffc108201d5d
- Size of remote file:
- 3.39 kB
- SHA256:
- c3a9fda2f4b08cd133b9aa0c2371eda3666ef0a26727263615f5286a41c5bf54
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