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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1747e2f741f04521bb7ef5a3a83699d297d2b3548f4c1c248658b7ae1552fc36
- Size of remote file:
- 438 MB
- SHA256:
- eab890d7c97d47fcb0d0fced9a7b60ae898bb6f043d6681cd1cad1197c42cabf
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