Text Classification
Transformers
PyTorch
English
deberta-v2
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/deberta-v3-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/deberta-v3-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/deberta-v3-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/deberta-v3-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/deberta-v3-base-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5deacf64dec672f2a1ffd46543b03672c6c294a0f9ea67ced445b81b5ebf43b
- Size of remote file:
- 3.5 kB
- SHA256:
- 88b935da2fc29ff764933e67ec9a25632110be5c295e82771fdd9768e4302e60
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