Datasets:
Convert dataset to Parquet
#1
by
mapama247
- opened
- README.md +606 -3
- wikihow_es.jsonl → adolescentes/train-00000-of-00001.parquet +2 -2
- all/train-00000-of-00001.parquet +3 -0
- arte-y-entretenimiento/train-00000-of-00001.parquet +3 -0
- automóviles-y-otros-vehículos/train-00000-of-00001.parquet +3 -0
- carreras-y-educación/train-00000-of-00001.parquet +3 -0
- comida-y-diversión/train-00000-of-00001.parquet +3 -0
- computadoras-y-electrónica/train-00000-of-00001.parquet +3 -0
- cuidado-y-estilo-personal/train-00000-of-00001.parquet +3 -0
- deportes/train-00000-of-00001.parquet +3 -0
- días-de-fiesta-y-tradiciones/train-00000-of-00001.parquet +3 -0
- en-el-trabajo/train-00000-of-00001.parquet +3 -0
- en-la-casa-y-el-jardín/train-00000-of-00001.parquet +3 -0
- filosofía-y-religión/train-00000-of-00001.parquet +3 -0
- finanzas-y-negocios/train-00000-of-00001.parquet +3 -0
- mascotas-y-animales/train-00000-of-00001.parquet +3 -0
- pasatiempos/train-00000-of-00001.parquet +3 -0
- relaciones/train-00000-of-00001.parquet +3 -0
- salud/train-00000-of-00001.parquet +3 -0
- viajes/train-00000-of-00001.parquet +3 -0
- vida-familiar/train-00000-of-00001.parquet +3 -0
- wikihow_es.py +0 -114
README.md
CHANGED
@@ -1,14 +1,14 @@
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---
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-
pretty_name: WikiHow-ES
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-
license: cc-by-nc-sa-3.0
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-
size_categories: 1K<n<10K
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language: es
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multilinguality: monolingual
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task_categories:
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- text-classification
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- question-answering
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- conversational
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- summarization
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tags:
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- Spanish
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- WikiHow
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@@ -16,6 +16,609 @@ tags:
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- Tutorials
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- Step-By-Step
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- Instruction Tuning
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19 |
---
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21 |
### Dataset Summary
|
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|
1 |
---
|
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|
|
|
|
|
2 |
language: es
|
3 |
+
license: cc-by-nc-sa-3.0
|
4 |
multilinguality: monolingual
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5 |
+
size_categories: 1K<n<10K
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6 |
task_categories:
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7 |
- text-classification
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8 |
- question-answering
|
9 |
- conversational
|
10 |
- summarization
|
11 |
+
pretty_name: WikiHow-ES
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12 |
tags:
|
13 |
- Spanish
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14 |
- WikiHow
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|
16 |
- Tutorials
|
17 |
- Step-By-Step
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18 |
- Instruction Tuning
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19 |
+
dataset_info:
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20 |
+
- config_name: adolescentes
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+
features:
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+
- name: category
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dtype: string
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+
- name: question
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+
dtype: string
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+
- name: introduction
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+
dtype: string
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28 |
+
- name: answers
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29 |
+
sequence: string
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+
- name: short_answers
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31 |
+
sequence: string
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32 |
+
- name: url
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33 |
+
dtype: string
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34 |
+
- name: num_answers
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35 |
+
dtype: int32
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36 |
+
- name: num_refs
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37 |
+
dtype: int32
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38 |
+
- name: expert_author
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39 |
+
dtype: bool
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40 |
+
splits:
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41 |
+
- name: train
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42 |
+
num_bytes: 1991245
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+
num_examples: 201
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+
download_size: 1153947
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+
dataset_size: 1991245
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+
- config_name: all
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+
features:
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+
- name: category
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+
dtype: string
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+
- name: question
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+
dtype: string
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52 |
+
- name: introduction
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+
dtype: string
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54 |
+
- name: answers
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+
sequence: string
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+
- name: short_answers
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+
sequence: string
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+
- name: url
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+
dtype: string
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60 |
+
- name: num_answers
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+
dtype: int32
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62 |
+
- name: num_refs
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+
dtype: int32
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64 |
+
- name: expert_author
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+
dtype: bool
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+
splits:
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+
- name: train
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+
num_bytes: 70513673
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+
num_examples: 7380
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+
download_size: 38605450
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+
dataset_size: 70513673
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+
- config_name: arte-y-entretenimiento
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+
features:
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+
- name: category
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+
dtype: string
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+
- name: question
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+
dtype: string
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+
- name: introduction
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+
dtype: string
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+
- name: answers
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+
sequence: string
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82 |
+
- name: short_answers
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+
sequence: string
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84 |
+
- name: url
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85 |
+
dtype: string
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86 |
+
- name: num_answers
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+
dtype: int32
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88 |
+
- name: num_refs
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89 |
+
dtype: int32
|
90 |
+
- name: expert_author
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91 |
+
dtype: bool
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+
splits:
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93 |
+
- name: train
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94 |
+
num_bytes: 2567138
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95 |
+
num_examples: 254
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96 |
+
download_size: 1438019
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97 |
+
dataset_size: 2567138
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98 |
+
- config_name: automóviles-y-otros-vehículos
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+
features:
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+
- name: category
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101 |
+
dtype: string
|
102 |
+
- name: question
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103 |
+
dtype: string
|
104 |
+
- name: introduction
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105 |
+
dtype: string
|
106 |
+
- name: answers
|
107 |
+
sequence: string
|
108 |
+
- name: short_answers
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109 |
+
sequence: string
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110 |
+
- name: url
|
111 |
+
dtype: string
|
112 |
+
- name: num_answers
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113 |
+
dtype: int32
|
114 |
+
- name: num_refs
|
115 |
+
dtype: int32
|
116 |
+
- name: expert_author
|
117 |
+
dtype: bool
|
118 |
+
splits:
|
119 |
+
- name: train
|
120 |
+
num_bytes: 890122
|
121 |
+
num_examples: 100
|
122 |
+
download_size: 480587
|
123 |
+
dataset_size: 890122
|
124 |
+
- config_name: carreras-y-educación
|
125 |
+
features:
|
126 |
+
- name: category
|
127 |
+
dtype: string
|
128 |
+
- name: question
|
129 |
+
dtype: string
|
130 |
+
- name: introduction
|
131 |
+
dtype: string
|
132 |
+
- name: answers
|
133 |
+
sequence: string
|
134 |
+
- name: short_answers
|
135 |
+
sequence: string
|
136 |
+
- name: url
|
137 |
+
dtype: string
|
138 |
+
- name: num_answers
|
139 |
+
dtype: int32
|
140 |
+
- name: num_refs
|
141 |
+
dtype: int32
|
142 |
+
- name: expert_author
|
143 |
+
dtype: bool
|
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+
splits:
|
145 |
+
- name: train
|
146 |
+
num_bytes: 6020903
|
147 |
+
num_examples: 564
|
148 |
+
download_size: 3261593
|
149 |
+
dataset_size: 6020903
|
150 |
+
- config_name: comida-y-diversión
|
151 |
+
features:
|
152 |
+
- name: category
|
153 |
+
dtype: string
|
154 |
+
- name: question
|
155 |
+
dtype: string
|
156 |
+
- name: introduction
|
157 |
+
dtype: string
|
158 |
+
- name: answers
|
159 |
+
sequence: string
|
160 |
+
- name: short_answers
|
161 |
+
sequence: string
|
162 |
+
- name: url
|
163 |
+
dtype: string
|
164 |
+
- name: num_answers
|
165 |
+
dtype: int32
|
166 |
+
- name: num_refs
|
167 |
+
dtype: int32
|
168 |
+
- name: expert_author
|
169 |
+
dtype: bool
|
170 |
+
splits:
|
171 |
+
- name: train
|
172 |
+
num_bytes: 3602835
|
173 |
+
num_examples: 454
|
174 |
+
download_size: 1866935
|
175 |
+
dataset_size: 3602835
|
176 |
+
- config_name: computadoras-y-electrónica
|
177 |
+
features:
|
178 |
+
- name: category
|
179 |
+
dtype: string
|
180 |
+
- name: question
|
181 |
+
dtype: string
|
182 |
+
- name: introduction
|
183 |
+
dtype: string
|
184 |
+
- name: answers
|
185 |
+
sequence: string
|
186 |
+
- name: short_answers
|
187 |
+
sequence: string
|
188 |
+
- name: url
|
189 |
+
dtype: string
|
190 |
+
- name: num_answers
|
191 |
+
dtype: int32
|
192 |
+
- name: num_refs
|
193 |
+
dtype: int32
|
194 |
+
- name: expert_author
|
195 |
+
dtype: bool
|
196 |
+
splits:
|
197 |
+
- name: train
|
198 |
+
num_bytes: 5457681
|
199 |
+
num_examples: 821
|
200 |
+
download_size: 2647916
|
201 |
+
dataset_size: 5457681
|
202 |
+
- config_name: cuidado-y-estilo-personal
|
203 |
+
features:
|
204 |
+
- name: category
|
205 |
+
dtype: string
|
206 |
+
- name: question
|
207 |
+
dtype: string
|
208 |
+
- name: introduction
|
209 |
+
dtype: string
|
210 |
+
- name: answers
|
211 |
+
sequence: string
|
212 |
+
- name: short_answers
|
213 |
+
sequence: string
|
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+
- name: url
|
215 |
+
dtype: string
|
216 |
+
- name: num_answers
|
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+
dtype: int32
|
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num_examples: 147
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download_size: 984068
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dataset_size: 1743050
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configs:
|
541 |
+
- config_name: adolescentes
|
542 |
+
data_files:
|
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- split: train
|
544 |
+
path: adolescentes/train-*
|
545 |
+
- config_name: all
|
546 |
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data_files:
|
547 |
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- split: train
|
548 |
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path: all/train-*
|
549 |
+
default: true
|
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- config_name: arte-y-entretenimiento
|
551 |
+
data_files:
|
552 |
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- split: train
|
553 |
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path: arte-y-entretenimiento/train-*
|
554 |
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- config_name: automóviles-y-otros-vehículos
|
555 |
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data_files:
|
556 |
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- split: train
|
557 |
+
path: automóviles-y-otros-vehículos/train-*
|
558 |
+
- config_name: carreras-y-educación
|
559 |
+
data_files:
|
560 |
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|
561 |
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path: carreras-y-educación/train-*
|
562 |
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- config_name: comida-y-diversión
|
563 |
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data_files:
|
564 |
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- split: train
|
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path: comida-y-diversión/train-*
|
566 |
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|
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data_files:
|
568 |
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|
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path: computadoras-y-electrónica/train-*
|
570 |
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|
571 |
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data_files:
|
572 |
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|
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path: cuidado-y-estilo-personal/train-*
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data_files:
|
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path: deportes/train-*
|
578 |
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|
579 |
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data_files:
|
580 |
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|
581 |
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path: días-de-fiesta-y-tradiciones/train-*
|
582 |
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|
583 |
+
data_files:
|
584 |
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|
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path: en-el-trabajo/train-*
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586 |
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|
587 |
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data_files:
|
588 |
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- split: train
|
589 |
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path: en-la-casa-y-el-jardín/train-*
|
590 |
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- config_name: filosofía-y-religión
|
591 |
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data_files:
|
592 |
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- split: train
|
593 |
+
path: filosofía-y-religión/train-*
|
594 |
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- config_name: finanzas-y-negocios
|
595 |
+
data_files:
|
596 |
+
- split: train
|
597 |
+
path: finanzas-y-negocios/train-*
|
598 |
+
- config_name: mascotas-y-animales
|
599 |
+
data_files:
|
600 |
+
- split: train
|
601 |
+
path: mascotas-y-animales/train-*
|
602 |
+
- config_name: pasatiempos
|
603 |
+
data_files:
|
604 |
+
- split: train
|
605 |
+
path: pasatiempos/train-*
|
606 |
+
- config_name: relaciones
|
607 |
+
data_files:
|
608 |
+
- split: train
|
609 |
+
path: relaciones/train-*
|
610 |
+
- config_name: salud
|
611 |
+
data_files:
|
612 |
+
- split: train
|
613 |
+
path: salud/train-*
|
614 |
+
- config_name: viajes
|
615 |
+
data_files:
|
616 |
+
- split: train
|
617 |
+
path: viajes/train-*
|
618 |
+
- config_name: vida-familiar
|
619 |
+
data_files:
|
620 |
+
- split: train
|
621 |
+
path: vida-familiar/train-*
|
622 |
---
|
623 |
|
624 |
### Dataset Summary
|
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cuidado-y-estilo-personal/train-00000-of-00001.parquet
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deportes/train-00000-of-00001.parquet
ADDED
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size 1028678
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días-de-fiesta-y-tradiciones/train-00000-of-00001.parquet
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size 534900
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en-el-trabajo/train-00000-of-00001.parquet
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en-la-casa-y-el-jardín/train-00000-of-00001.parquet
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filosofía-y-religión/train-00000-of-00001.parquet
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finanzas-y-negocios/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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mascotas-y-animales/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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pasatiempos/train-00000-of-00001.parquet
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size 3430327
|
relaciones/train-00000-of-00001.parquet
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|
salud/train-00000-of-00001.parquet
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size 4538289
|
viajes/train-00000-of-00001.parquet
ADDED
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|
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version https://git-lfs.github.com/spec/v1
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size 851347
|
vida-familiar/train-00000-of-00001.parquet
ADDED
@@ -0,0 +1,3 @@
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|
1 |
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version https://git-lfs.github.com/spec/v1
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size 984068
|
wikihow_es.py
DELETED
@@ -1,114 +0,0 @@
|
|
1 |
-
import os
|
2 |
-
import re
|
3 |
-
import csv
|
4 |
-
import json
|
5 |
-
import datasets
|
6 |
-
|
7 |
-
_DESCRIPTION = "Spanish articles from WikiHow"
|
8 |
-
_HOMEPAGE = "https://www.wikihow.com"
|
9 |
-
_LICENSE = "CC BY-NC-SA 3.0"
|
10 |
-
_VERSION = "1.1.0"
|
11 |
-
|
12 |
-
_DATAPATH = "wikihow_es.jsonl"
|
13 |
-
|
14 |
-
_CATEGORIES = [
|
15 |
-
"salud",
|
16 |
-
"viajes",
|
17 |
-
"deportes",
|
18 |
-
"relaciones",
|
19 |
-
"pasatiempos",
|
20 |
-
"adolescentes",
|
21 |
-
"vida-familiar",
|
22 |
-
"en-el-trabajo",
|
23 |
-
"comida-y-diversión",
|
24 |
-
"finanzas-y-negocios",
|
25 |
-
"mascotas-y-animales",
|
26 |
-
"carreras-y-educación",
|
27 |
-
"filosofía-y-religión",
|
28 |
-
"arte-y-entretenimiento",
|
29 |
-
"en-la-casa-y-el-jardín",
|
30 |
-
"cuidado-y-estilo-personal",
|
31 |
-
"computadoras-y-electrónica",
|
32 |
-
"días-de-fiesta-y-tradiciones",
|
33 |
-
"automóviles-y-otros-vehículos",
|
34 |
-
]
|
35 |
-
|
36 |
-
def format_methods(methods, short=False):
|
37 |
-
EOL = "\n" if short else "\n\n"
|
38 |
-
formatted = []
|
39 |
-
for method in methods:
|
40 |
-
if method["title"].lower() != "pasos":
|
41 |
-
content = f"Método {method['number']}: {method['title']}{EOL}"
|
42 |
-
else:
|
43 |
-
content = f"Sigue los siguientes pasos:{EOL}"
|
44 |
-
for step in method["steps"]:
|
45 |
-
step_content = re.sub(r"\n+", "\n", step).strip()
|
46 |
-
if short:
|
47 |
-
step_content = step_content.split("\n")[0]
|
48 |
-
content += step_content + EOL
|
49 |
-
formatted.append(content.strip())
|
50 |
-
return formatted
|
51 |
-
|
52 |
-
|
53 |
-
class WikiHowEs(datasets.GeneratorBasedBuilder):
|
54 |
-
""" WikiHowEs: Collection of Spanish tutorials. """
|
55 |
-
|
56 |
-
VERSION = datasets.Version(_VERSION)
|
57 |
-
|
58 |
-
DEFAULT_CONFIG_NAME = "all"
|
59 |
-
BUILDER_CONFIGS = [datasets.BuilderConfig(name="all", version=VERSION, description="All articles from WikiHow-ES.")]
|
60 |
-
for _CAT in _CATEGORIES:
|
61 |
-
BUILDER_CONFIGS.append(
|
62 |
-
datasets.BuilderConfig(name=_CAT, version=VERSION, description=f"Articles from the category {_CAT}")
|
63 |
-
)
|
64 |
-
|
65 |
-
@staticmethod
|
66 |
-
def _info():
|
67 |
-
features = datasets.Features(
|
68 |
-
{
|
69 |
-
"category": datasets.Value("string"),
|
70 |
-
"question": datasets.Value("string"),
|
71 |
-
"introduction": datasets.Value("string"),
|
72 |
-
"answers": datasets.features.Sequence(datasets.Value("string")),
|
73 |
-
"short_answers": datasets.features.Sequence(datasets.Value("string")),
|
74 |
-
"url": datasets.Value("string"),
|
75 |
-
"num_answers": datasets.Value("int32"),
|
76 |
-
"num_refs": datasets.Value("int32"),
|
77 |
-
"expert_author": datasets.Value("bool"),
|
78 |
-
}
|
79 |
-
)
|
80 |
-
return datasets.DatasetInfo(
|
81 |
-
description=_DESCRIPTION,
|
82 |
-
features=features,
|
83 |
-
homepage=_HOMEPAGE,
|
84 |
-
license=_LICENSE,
|
85 |
-
)
|
86 |
-
|
87 |
-
@staticmethod
|
88 |
-
def _split_generators(dl_manager):
|
89 |
-
data_dir = dl_manager.download_and_extract(_DATAPATH)
|
90 |
-
return [
|
91 |
-
datasets.SplitGenerator(
|
92 |
-
name=datasets.Split.TRAIN,
|
93 |
-
gen_kwargs={
|
94 |
-
"filepath": data_dir,
|
95 |
-
},
|
96 |
-
),
|
97 |
-
]
|
98 |
-
|
99 |
-
def _generate_examples(self, filepath):
|
100 |
-
with open(filepath, encoding="utf-8") as f:
|
101 |
-
for key, row in enumerate(f):
|
102 |
-
data = json.loads(row)
|
103 |
-
if self.config.name in ["all", data["category"].lower()]:
|
104 |
-
yield key, {
|
105 |
-
"category": data["category"],
|
106 |
-
"question": f"¿{data['title']}?",
|
107 |
-
"introduction": data["intro"],
|
108 |
-
"answers": format_methods(data["methods"], short=False),
|
109 |
-
"short_answers": format_methods(data["methods"], short=True),
|
110 |
-
"num_answers": data["num_methods"],
|
111 |
-
"num_refs": data["num_refs"],
|
112 |
-
"expert_author": data["expert_author"],
|
113 |
-
"url": data["url"],
|
114 |
-
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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