Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__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-something__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-something__round-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-1") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-something__round-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5f35125fbd3820f52cabd3abeda1b74b7e039dcdf993e2aee07fd44b6c2f1e5
- Size of remote file:
- 3.39 kB
- SHA256:
- b1ec253105f8347d995757a33e0f5091cc45f6f7827e361af7c2335eacb26f03
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