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--- |
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widget: |
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- text: "I believe I will get into UW. </s></s> I will get into UW." |
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--- |
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This is an off-the-shelf roberta-large model finetuned on WANLI, the Worker-AI Collaborative NLI dataset ([Liu et al., 2022](https://arxiv.org/abs/2201.05955)). It outperforms the `roberta-large-mnli` model on seven out-of-domain test sets, including by 11% on HANS and 9% on Adversarial NLI. |
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### How to use |
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```python |
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from transformers import RobertaTokenizer, RobertaForSequenceClassification |
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model = RobertaForSequenceClassification.from_pretrained('alisawuffles/roberta-large-wanli') |
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tokenizer = RobertaTokenizer.from_pretrained('alisawuffles/roberta-large-wanli') |
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x = tokenizer("I believe I will get into UW.", "I will get into UW.", hypothesis, return_tensors='pt', max_length=128, truncation=True) |
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logits = model(**x).logits |
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probs = logits.softmax(dim=1).squeeze(0) |
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label_id = torch.argmax(probs).item() |
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prediction = model.config.id2label[label_id] |
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``` |
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### Citation |
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``` |
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@misc{liu-etal-2022-wanli, |
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title = "WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation", |
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author = "Liu, Alisa and |
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Swayamdipta, Swabha and |
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Smith, Noah A. and |
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Choi, Yejin", |
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month = jan, |
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year = "2022", |
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url = "https://arxiv.org/pdf/2201.05955", |
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} |
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``` |
