Datasets:
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---
configs:
- config_name: BoolQ_train
data_files: "BoolQ/train.jsonl"
- config_name: BoolQ_unlabeled
data_files: "BoolQ/unlabeled.jsonl"
- config_name: CB_train
data_files: "CB/train.jsonl"
- config_name: CB_unlabeled
data_files: "CB/unlabeled.jsonl"
- config_name: COPA_train
data_files: "COPA/train.jsonl"
- config_name: COPA_unlabeled
data_files: "COPA/unlabeled.jsonl"
- config_name: MultiRC_train
data_files: "MultiRC/train.jsonl"
- config_name: MultiRC_unlabeled
data_files: "MultiRC/unlabeled.jsonl"
- config_name: RTE_train
data_files: "RTE/train.jsonl"
- config_name: RTE_unlabeled
data_files: "RTE/unlabeled.jsonl"
- config_name: ReCoRD_train
data_files: "ReCoRD/train.jsonl"
- config_name: ReCoRD_unlabeled
data_files: "ReCoRD/unlabeled.jsonl"
- config_name: WSC_train
data_files: "WSC/train.jsonl"
- config_name: WSC_unlabeled
data_files: "WSC/unlabeled.jsonl"
- config_name: WiC_train
data_files: "WiC/train.jsonl"
- config_name: WiC_unlabeled
data_files: "WiC/unlabeled.jsonl"
---
# [FewGLUE](https://arxiv.org/abs/2009.07118)
FewGLUE dataset, consisting of a random selection of 32 training examples from the SuperGLUE training sets and up to 20,000 unlabeled examples for each SuperGLUE task.
[Adapted from Original Repository](https://github.com/timoschick/fewglue)
## 📕 Citation
```misc
@article{schick2020small,
title={It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners},
author={Timo Schick and Hinrich Schütze},
journal={Computing Research Repository},
volume={arXiv:2009.07118},
url={http://arxiv.org/abs/2009.07118},
year={2020}
}
```
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