Instructions to use DeepPavlov/roberta-large-winogrande with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepPavlov/roberta-large-winogrande with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DeepPavlov/roberta-large-winogrande")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/roberta-large-winogrande") model = AutoModelForSequenceClassification.from_pretrained("DeepPavlov/roberta-large-winogrande") - Notebooks
- Google Colab
- Kaggle
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README.md
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### How to use
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### BibTeX entry and citation info
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```bibtex
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### How to use
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## Training data
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[WinoGrande-XL](https://huggingface.co/datasets/winogrande) reformatted the following way:
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1. Each sentence was split on `_` placeholder symbol.
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2. Each option was concatenated with the second part of the split, thus transforming each example into two text segment pairs.
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3. Text segment pairs corresponding to correct and incorrect options were marked with `True` and `False` labels accordingly.
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4. Text segment pairs were shuffled thereafter.
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### BibTeX entry and citation info
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```bibtex
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