Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Instructions to use NDugar/v3large-1epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/v3large-1epoch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/v3large-1epoch")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/v3large-1epoch") model = AutoModelForSequenceClassification.from_pretrained("NDugar/v3large-1epoch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3558cc94447a539f0f683dae55d37f871265cbca769e56cd2a22b0db5cce33c1
- Size of remote file:
- 1.74 GB
- SHA256:
- ced5efa4b8b24ddeeba8b0d5884ac47af7b00aaf5fe0ea97be2a53ea418301b9
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