Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt 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-bt 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-bt")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-bt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fc84633376baf2235b188ed13543345e72efd2c007772a0bf1cd3bba2a68e1e
- Size of remote file:
- 3.39 kB
- SHA256:
- 15748c6daf6532490bebc17cf4a0499da8284eed25cc759d40010f47b842e452
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