Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-None__round-1 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-None__round-1 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-None__round-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-None__round-1") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-None__round-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2cf7a270b13ef9c438fd80daf8e31d0c55537b613cb7d88f3a8907b0bca6464
- Size of remote file:
- 438 MB
- SHA256:
- f49e1347be6ea5531be8c17024a48d0766986f22dcd79509cb41074c19017d6a
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