Instructions to use BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rsa 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-rsa 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-rsa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rsa") model = AutoModelForSequenceClassification.from_pretrained("BenjaminOcampo/task-implicit_task__model-hatebert__aug_method-rsa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdac4a9eb8337cad32e7d88c7c51018f70d8e6779a55d9608f40ed9eb79b7c72
- Size of remote file:
- 3.39 kB
- SHA256:
- 1ed0d4ceed3aac06f31eee93c285cc7f4d50a253dc43cf16cbbaffce7333e617
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.