Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rne 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-rne 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-rne")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rne") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rne") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c52eaeeb03dbc2a0ffce3959fb2869dd496e843b441374d13a849e417b5ed89c
- Size of remote file:
- 3.39 kB
- SHA256:
- 0ae97d9ebb25fc150b595090c6372cb23102f60661c807fa9ec44d8d2aea5079
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