Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all 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-all 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-all")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-all") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81178e93c0eb895fb01b0adefc84356390876d65fbfe2bfa191e58d18899d602
- Size of remote file:
- 3.39 kB
- SHA256:
- c3cfc3cb4f075b5eaf49e0272d2269a8b7caf6878a8c23eb824ccf431db1e7b7
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