Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v1
deberta-mnli
Instructions to use NDugar/ZSD-microsoft-v2xxlmnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/ZSD-microsoft-v2xxlmnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/ZSD-microsoft-v2xxlmnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/ZSD-microsoft-v2xxlmnli") model = AutoModelForSequenceClassification.from_pretrained("NDugar/ZSD-microsoft-v2xxlmnli") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0446ed9be46d0a6c8be7b6e94744c407dd2982326a8288f4c648cb249806c4b8
- Size of remote file:
- 3.13 GB
- SHA256:
- 5b2d8ddf6c80e4e6105b27cdb9fa346a8ba1f0c0dfd410b0007be894567cb4db
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