Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-aav 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-aav 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-aav")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-aav") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-aav") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2d991118ee3845d2594c0882d13d07d83e46bcb4960f4815f64c872d9807914
- Size of remote file:
- 438 MB
- SHA256:
- f466ce4fe43fa0f608bddb2588c5f4427be1d5f41e49a709607109f1bf3f397d
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