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README.md
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---
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license: cc-by-4.0
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dataset_info:
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- config_name: winogrande_m
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features:
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- name: sentence
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download_size: 215301
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dataset_size: 412504
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configs:
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- config_name: winogrande_m
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data_files:
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- split: train
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---
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license: cc-by-4.0
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dataset_info:
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- config_name: winogrande_l
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features:
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- name: sentence
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dtype: string
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- name: option1
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dtype: string
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- name: option2
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dtype: string
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- name: answer
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dtype: string
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splits:
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- name: train
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num_bytes: 1319544
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num_examples: 10234
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- name: test
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num_bytes: 227633
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num_examples: 1767
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- name: validation
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num_bytes: 164183
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num_examples: 1267
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download_size: 733064
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dataset_size: 1711360
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- config_name: winogrande_m
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features:
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- name: sentence
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download_size: 215301
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dataset_size: 412504
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configs:
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- config_name: winogrande_l
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data_files:
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- split: train
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path: winogrande_l/train-*
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- split: test
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path: winogrande_l/test-*
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- split: validation
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path: winogrande_l/validation-*
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- config_name: winogrande_m
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data_files:
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- split: train
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dataset_infos.json
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"features": {
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"sentence": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"option1": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"option2": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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},
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"answer": {
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"dtype": "string",
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"id": null,
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"_type": "Value"
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}
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},
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"
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"
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"builder_name": "winogrande",
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"config_name": "winogrande_l",
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"version": {
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"version_str": "1.1.0",
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"splits": {
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"train": {
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"name": "train",
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"num_bytes":
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"num_examples": 10234,
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"dataset_name":
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},
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"test": {
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"name": "test",
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"num_bytes":
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"num_examples": 1767,
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"dataset_name":
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},
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"validation": {
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"name": "validation",
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"num_bytes":
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"num_examples": 1267,
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"dataset_name":
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}
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},
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"download_checksums": {
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"https://storage.googleapis.com/ai2-mosaic/public/winogrande/winogrande_1.1.zip": {
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"num_bytes": 3395492,
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"checksum": "3619ab104d8be2977b25c90ff420cb42d491707dcc75362a1e5d22bc082b7318"
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}
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},
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"download_size":
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"
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"
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"size_in_bytes": 5106916
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},
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"winogrande_xl": {
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"description": "WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern\n 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a\nfill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires\ncommonsense reasoning.\n",
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"features": {
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"sentence": {
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"dtype": "string",
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"_type": "Value"
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},
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"option1": {
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"dtype": "string",
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"_type": "Value"
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},
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"option2": {
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"dtype": "string",
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"_type": "Value"
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},
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"answer": {
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"dtype": "string",
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"_type": "Value"
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}
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},
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"builder_name": "winogrande_raw",
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"dataset_name": "winogrande_raw",
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"config_name": "winogrande_l",
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"version": {
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"version_str": "1.1.0",
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 1319544,
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"num_examples": 10234,
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"dataset_name": null
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},
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"test": {
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"name": "test",
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"num_bytes": 227633,
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"num_examples": 1767,
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"dataset_name": null
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},
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"validation": {
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"name": "validation",
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"num_bytes": 164183,
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"num_examples": 1267,
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"dataset_name": null
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}
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},
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"download_size": 733064,
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"dataset_size": 1711360,
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"size_in_bytes": 2444424
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},
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"winogrande_xl": {
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"description": "WinoGrande is a new collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern\n 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a\nfill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires\ncommonsense reasoning.\n",
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winogrande_l/test-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:3a7c4b062ec4540d55751c581bf66d40299cb9637778143bb73dce07beb615d5
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size 117656
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winogrande_l/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:49600aec4c30f3da610232ab1718bb2134d5d9beb0aa5543ee693453f27df181
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size 529480
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winogrande_l/validation-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:76bf48df35738da9100407a9272f5aad11791a98642c6611f7593a0bb9a48601
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size 85928
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