Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v1
deberta-mnli
Instructions to use NDugar/v3-Large-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/v3-Large-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/v3-Large-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/v3-Large-mnli") model = AutoModelForSequenceClassification.from_pretrained("NDugar/v3-Large-mnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d038a2b267caa8f000304c8f6e77105aaef20f0a7e2455608ad49fd38cde8250
- Size of remote file:
- 1.74 GB
- SHA256:
- b2723410e9906cee3b3636c827dcdd99e3badcb98768693a5dd20f6b4b7d8c91
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