Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-None__round-1 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-None__round-1 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-None__round-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-None__round-1") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-None__round-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66db841639d8e83672c1b5eff34218a438f50a1a954ca39deee51c19108f406e
- Size of remote file:
- 438 MB
- SHA256:
- fba8da1cf34cf88395bf0face4feb80199ad4b47801495a0be2b9d97ce2cd696
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