Zero-Shot Classification
Transformers
PyTorch
ONNX
Safetensors
deberta-v2
text-classification
nli
Eval Results (legacy)
Instructions to use MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7") model = AutoModelForSequenceClassification.from_pretrained("MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7") - Inference
- Notebooks
- Google Colab
- Kaggle
Ctrl+K