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:
- 52de81392d7fc6a36dd882c5f99bfa8bb895220b3bffe4dd649003fe76a5a399
- Size of remote file:
- 738 MB
- SHA256:
- bc5014fcb029b15c1842c71e95a4c931cf7f854170cdf3b08c1f25ae5479ee4c
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