参考：
plain_text
使用以下命令在 TFDS 中加载此数据集：
ds = tfds.load('huggingface:anli/plain_text')
- 说明：
The Adversarial Natural Language Inference (ANLI) is a new large-scale NLI benchmark dataset,
The dataset is collected via an iterative, adversarial human-and-model-in-the-loop procedure.
ANLI is much more difficult than its predecessors including SNLI and MNLI.
It contains three rounds. Each round has train/dev/test splits.
- 许可：无已知许可
- 版本：0.1.0
- 拆分：
| 拆分 | 样本 |
|---|---|
'dev_r1' |
1000 |
'dev_r2' |
1000 |
'dev_r3' |
1200 |
'test_r1' |
1000 |
'test_r2' |
1000 |
'test_r3' |
1200 |
'train_r1' |
16946 |
'train_r2' |
45460 |
'train_r3' |
100459 |
- 特征：
{
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"_type": "Value"
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"premise": {
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"hypothesis": {
"dtype": "string",
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"_type": "Value"
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"label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
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],
"names_file": null,
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"_type": "ClassLabel"
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"reason": {
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