Zero-Shot Classification
Transformers
PyTorch
English
deberta-v2
text-classification
deberta-v3
deberta-v2`
deberta-mnli
Instructions to use NDugar/1epochv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NDugar/1epochv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="NDugar/1epochv3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NDugar/1epochv3") model = AutoModelForSequenceClassification.from_pretrained("NDugar/1epochv3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56289df0781710863fb0d61ddc445b7474a64200aca1ce7800d1e323cb3ac126
- Size of remote file:
- 3.48 GB
- SHA256:
- c0ff7139d733ef00ec2fab30f1819042f38db12865d7f324fbe7018b87e7526a
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