Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm_revised 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-gm_revised 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-gm_revised")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm_revised") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-gm_revised", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 805b774ab5e2bb3b9a7c7344b9081dd71b44af2ec092cf2ab91fc18a5c8a2029
- Size of remote file:
- 3.39 kB
- SHA256:
- 168398b2ad11ab9c0367a7deb6e654847c58e8b91f943a95b3c0a2144b9c184c
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