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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d849c36cc2ba9da62c4a098ea7bb04cbe90913560a6a9fbff5b594749b370be6
- Size of remote file:
- 3.39 kB
- SHA256:
- ea5631d995954a6a33a24846073c7b58b7a8ab1f141a077a332ed466ff4f9fc6
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