Instructions to use sileod/deberta-v3-base-tasksource-paraphrase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-base-tasksource-paraphrase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-paraphrase")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-base-tasksource-paraphrase") model = AutoModelForSequenceClassification.from_pretrained("sileod/deberta-v3-base-tasksource-paraphrase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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datasets:
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- nyu-mll/glue
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- paws
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- hlgd
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language:
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- en
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---
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| Dataset Name | Test Accuracy |
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|--------------------------|---------------|
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| glue/mrpc | 0.856 |
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| glue/qqp | 0.876 |
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| hlgd | 0.898 |
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| paws/labeled_final | 0.952 |
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| paws/labeled_swap | 0.968 |
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| medical_questions_pairs | 0.8562 |
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| parade | 0.732 |
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| apt | 0.824 |
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