Add README.md

README.md

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+---
+language:
+- en
+tags:
+- text2text-generation
+license: mit
+datasets:
+- wikifactcheck
+widget:
+- text: "Little Miss Sunshine was filmed over 30 days."
+---
+# BART base negative claim generation model
+
+This is a BART-based model fine-tuned for negative claim generation. This model is used in the data augmentation process described in the paper [CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models](https://arxiv.org/abs/2109.15107). The model has been fine-tuned using the parallel and opposing claims from WikiFactCheck-English dataset.
+
+## Usage
+
+```
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_name = 'minwhoo/bart-base-negative-claim-generation'
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+model.to('cuda' if torch.cuda.is_available() else 'cpu')
+
+examples = [
+    "Little Miss Sunshine was filmed over 30 days.",
+    "Magic Johnson did not play for the Lakers.",
+    "Claire Danes is wedded to an actor from England."
+]
+
+batch = tokenizer(examples, max_length=1024, padding=True, truncation=True, return_tensors="pt")
+out = model.generate(batch['input_ids'].to(model.device), num_beams=5)
+negative_examples = tokenizer.batch_decode(out, skip_special_tokens=True)
+print(negative_examples)
+# ['Little Miss Sunshine was filmed less than 3 days.', 'Magic Johnson played for the Lakers.', 'Claire Danes is married to an actor from France.']
+```
+
+## Citation
+
+```
+@inproceedings{lee2021crossaug,
+  title={CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models},
+  author={Minwoo Lee and Seungpil Won and Juae Kim and Hwanhee Lee and Cheoneum Park and Kyomin Jung},
+  booktitle={Proceedings of the 30th ACM International Conference on Information & Knowledge Management},
+  publisher={Association for Computing Machinery},
+  series={CIKM '21},
+  year={2021}
+}
+```