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albertvillanova HF staff commited on
Commit
6429127
1 Parent(s): 1dde59d

Add determiner_noun_agreement_with_adj_irregular_1 data files

Browse files
README.md CHANGED
@@ -436,10 +436,10 @@ dataset_info:
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  dtype: int32
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  splits:
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  - name: train
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- num_bytes: 185924
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  num_examples: 1000
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- download_size: 499664
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- dataset_size: 185924
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  - config_name: determiner_noun_agreement_with_adj_irregular_2
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  features:
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  - name: sentence_good
@@ -1953,6 +1953,10 @@ configs:
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  data_files:
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  - split: train
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  path: determiner_noun_agreement_with_adj_2/train-*
 
 
 
 
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  ---
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  # Dataset Card for "blimp"
 
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  dtype: int32
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  splits:
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  - name: train
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+ num_bytes: 184529
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  num_examples: 1000
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+ download_size: 54405
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+ dataset_size: 184529
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  - config_name: determiner_noun_agreement_with_adj_irregular_2
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  features:
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  - name: sentence_good
 
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  data_files:
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  - split: train
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  path: determiner_noun_agreement_with_adj_2/train-*
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+ - config_name: determiner_noun_agreement_with_adj_irregular_1
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+ data_files:
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+ - split: train
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+ path: determiner_noun_agreement_with_adj_irregular_1/train-*
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  ---
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  # Dataset Card for "blimp"
dataset_infos.json CHANGED
@@ -959,62 +959,50 @@
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  "features": {
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  "sentence_good": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  "field": {
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  "linguistics_term": {
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  "dtype": "string",
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  "_type": "Value"
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  "UID": {
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  "_type": "Value"
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  "dtype": "bool",
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  "one_prefix_method": {
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  "two_prefix_method": {
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  "lexically_identical": {
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  "dtype": "bool",
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  "pair_id": {
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  "dtype": "int32",
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- "id": null,
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  "_type": "Value"
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  }
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  },
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- "supervised_keys": null,
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  "builder_name": "blimp",
 
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  "config_name": "determiner_noun_agreement_with_adj_irregular_1",
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  "version": {
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  "version_str": "0.1.0",
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- "description": null,
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- "datasets_version_to_prepare": null,
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  "major": 0,
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  "minor": 1,
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  "patch": 0
@@ -1022,20 +1010,14 @@
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  "splits": {
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  "train": {
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  "name": "train",
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- "num_bytes": 185924,
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  "num_examples": 1000,
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- "dataset_name": "blimp"
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- }
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- },
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- "download_checksums": {
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- "https://raw.githubusercontent.com/alexwarstadt/blimp/master/data/determiner_noun_agreement_with_adj_irregular_1.jsonl": {
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- "checksum": "1f4c6e42a48f4220afec629679641479feac3883cd7fa346d9e9e129cd7e8f55"
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- "download_size": 499664,
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- "dataset_size": 185924,
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- "size_in_bytes": 685588
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  },
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  "determiner_noun_agreement_with_adj_irregular_2": {
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  "description": "\nBLiMP is a challenge set for evaluating what language models (LMs) know about\nmajor grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each\ncontaining 1000 minimal pairs isolating specific contrasts in syntax,\nmorphology, or semantics. The data is automatically generated according to\nexpert-crafted grammars.\n",
 
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  "features": {
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  "sentence_good": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "sentence_bad": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "field": {
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  "dtype": "string",
 
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  "_type": "Value"
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  "linguistics_term": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "UID": {
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  "dtype": "string",
 
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  "_type": "Value"
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  },
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  "simple_LM_method": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  },
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  "one_prefix_method": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  },
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  "two_prefix_method": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  },
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  "lexically_identical": {
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  "dtype": "bool",
 
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  "_type": "Value"
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  },
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  "pair_id": {
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  "dtype": "int32",
 
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  "_type": "Value"
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  }
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  },
 
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  "builder_name": "blimp",
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+ "dataset_name": "blimp",
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  "config_name": "determiner_noun_agreement_with_adj_irregular_1",
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  "version": {
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  "version_str": "0.1.0",
 
 
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  "major": 0,
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  "minor": 1,
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  "patch": 0
 
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  "splits": {
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  "train": {
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  "name": "train",
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+ "num_bytes": 184529,
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  "num_examples": 1000,
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+ "dataset_name": null
 
 
 
 
 
 
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  }
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  },
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+ "download_size": 54405,
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+ "dataset_size": 184529,
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+ "size_in_bytes": 238934
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  },
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  "determiner_noun_agreement_with_adj_irregular_2": {
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  "description": "\nBLiMP is a challenge set for evaluating what language models (LMs) know about\nmajor grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each\ncontaining 1000 minimal pairs isolating specific contrasts in syntax,\nmorphology, or semantics. The data is automatically generated according to\nexpert-crafted grammars.\n",
determiner_noun_agreement_with_adj_irregular_1/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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