Instructions to use Deehan1866/deberta-wic-angle3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deehan1866/deberta-wic-angle3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Deehan1866/deberta-wic-angle3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Deehan1866/deberta-wic-angle3") model = AutoModelForSequenceClassification.from_pretrained("Deehan1866/deberta-wic-angle3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc8f04c0ad32f6a6d072ac64d4af07a808d2d4bffbc49f86a757705b9cca50e2
- Size of remote file:
- 5.91 kB
- SHA256:
- abafb44fe171cd9bdda6813e3662da3dc66d66e070cda26638b9dc0c0337e7eb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.