Instructions to use microsoft/deberta-xlarge-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-xlarge-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/deberta-xlarge-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-xlarge-mnli") model = AutoModelForSequenceClassification.from_pretrained("microsoft/deberta-xlarge-mnli") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8f6fa2b24aa583bbedf6ab041c32563b85eda89a4caf859363bc7467c385b9c
- Size of remote file:
- 3.04 GB
- SHA256:
- 60a1cac3b855e6994dd09daee5f697bd13f34bc1bada78d60844574872b092c3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.