Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda 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-eda 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-eda")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-eda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 545530be7a2d721d5bc178180b0dc1735abd0c80ad6ab1b90d140206465ceced
- Size of remote file:
- 3.39 kB
- SHA256:
- c54be84128ffab13d0bb787e8e6ebd31e12fde0a4548a0565c85bfd9e0c12162
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