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Delete legacy dataset_infos.json
Browse files- dataset_infos.json +0 -86
dataset_infos.json
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{
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"default": {
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"description": "The Multi-Genre Natural Language Inference (MultiNLI) corpus is a\ncrowd-sourced collection of 433k sentence pairs annotated with textual\nentailment information. The corpus is modeled on the SNLI corpus, but differs in\nthat covers a range of genres of spoken and written text, and supports a\ndistinctive cross-genre generalization evaluation. The corpus served as the\nbasis for the shared task of the RepEval 2017 Workshop at EMNLP in Copenhagen.\n",
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"citation": "@InProceedings{N18-1101,\n author = {Williams, Adina\n and Nangia, Nikita\n and Bowman, Samuel},\n title = {A Broad-Coverage Challenge Corpus for\n Sentence Understanding through Inference},\n booktitle = {Proceedings of the 2018 Conference of\n the North American Chapter of the\n Association for Computational Linguistics:\n Human Language Technologies, Volume 1 (Long\n Papers)},\n year = {2018},\n publisher = {Association for Computational Linguistics},\n pages = {1112--1122},\n location = {New Orleans, Louisiana},\n url = {http://aclweb.org/anthology/N18-1101}\n}\n",
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"homepage": "https://www.nyu.edu/projects/bowman/multinli/",
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"license": "",
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"features": {
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"promptID": {
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"dtype": "int32",
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"_type": "Value"
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},
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"pairID": {
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"dtype": "string",
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"_type": "Value"
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},
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"premise": {
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"dtype": "string",
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"_type": "Value"
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},
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"premise_binary_parse": {
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"dtype": "string",
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"_type": "Value"
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},
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"premise_parse": {
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"dtype": "string",
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"_type": "Value"
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},
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"hypothesis": {
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"dtype": "string",
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"_type": "Value"
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},
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"hypothesis_binary_parse": {
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"dtype": "string",
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"_type": "Value"
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},
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"hypothesis_parse": {
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"dtype": "string",
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"_type": "Value"
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},
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"genre": {
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"dtype": "string",
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"_type": "Value"
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},
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"label": {
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"names": [
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"entailment",
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"neutral",
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"contradiction"
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],
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"_type": "ClassLabel"
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}
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},
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"builder_name": "multi_nli",
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"dataset_name": "multi_nli",
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"config_name": "default",
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"version": {
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"version_str": "0.0.0",
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"major": 0,
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"minor": 0,
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"patch": 0
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},
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 410210306,
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"num_examples": 392702,
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"dataset_name": null
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},
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"validation_matched": {
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"name": "validation_matched",
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"num_bytes": 10063907,
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"num_examples": 9815,
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"dataset_name": null
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},
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"validation_mismatched": {
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"name": "validation_mismatched",
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"num_bytes": 10610189,
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"num_examples": 9832,
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"dataset_name": null
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}
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},
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"download_size": 224005223,
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"dataset_size": 430884402,
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"size_in_bytes": 654889625
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}
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}
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