Hugging Face's logo

Datasets:
Sirawipa
/
hosxp_time_code

Modalities:
Text
Formats:
parquet
Size:
< 1K
Libraries:
Datasets
pandas
Dataset card Data Studio Files
xet
Community
2
librarian-bot commited on
Commit
5bba83e
·
verified ·
1 Parent(s): 52a62f1

Librarian Bot: Add language metadata for dataset

Browse files

This pull request aims to enrich the metadata of your dataset by adding language metadata to `YAML` block of your dataset card `README.md`.

How did we find this information?

- The librarian-bot downloaded a sample of rows from your dataset using the [dataset-server](https://huggingface.co/docs/datasets-server/) library
- The librarian-bot used a language detection model to predict the likely language of your dataset. This was done on columns likely to contain text data.
- Predictions for rows are aggregated by language and a filter is applied to remove languages which are very infrequently predicted
- A confidence threshold is applied to remove languages which are not confidently predicted

The following languages were detected with the following mean probabilities:

- Thai (th): 98.34%


If this PR is merged, the language metadata will be added to your dataset card. This will allow users to filter datasets by language on the [Hub](https://huggingface.co/datasets).
If the language metadata is incorrect, please feel free to close this PR.

To merge this PR, you can use the merge button below the PR:
![Screenshot 2024-02-06 at 15.27.46.png](https://cdn-uploads.huggingface.co/production/uploads/63d3e0e8ff1384ce6c5dd17d/1PRE3CoDpg_wfThC6U1w0.png)

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bots). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to

@davanstrien
.

Files changed (1) hide show
  1. README.md +265 -263
README.md CHANGED
@@ -1,4 +1,6 @@
1
  ---
 
 
2
  dataset_info:
3
  features:
4
  - name: text
@@ -6,269 +8,269 @@ dataset_info:
6
  - name: label
7
  dtype:
8
  class_label:
9
- names:
10
- '0': 0.5AE
11
- '1': 0.5HS2
12
- '2': 0.5HS3
13
- '3': 0.5PE
14
- '4': 0.5PN
15
- '5': 0.5SSU
16
- '6': 0
17
- '7': 1.5SSU
18
- '8': 10
19
- '9': 10.3
20
- '10': 1022
21
- '11': 11
22
- '12': 11.3
23
- '13': 1123
24
- '14': 11AE
25
- '15': 11AN
26
- '16': 11PE
27
- '17': 11PN
28
- '18': 12
29
- '19': 12.3
30
- '20': 1224
31
- '21': 12T
32
- '22': 15min
33
- '23': 18.3
34
- '24': 19.3
35
- '25': 1AC
36
- '26': 1AC1
37
- '27': 1AE
38
- '28': 1AN
39
- '29': 1HR
40
- '30': 1HS
41
- '31': 1HS2
42
- '32': 1HS3
43
- '33': 1KP
44
- '34': 1PC
45
- '35': 1PE
46
- '36': 1PN
47
- '37': 1PNE
48
- '38': 1SSU
49
- '39': 1WM
50
- '40': 20.3
51
- '41': 21.3
52
- '42': 22.3
53
- '43': 23.3
54
- '44': 24
55
- '45': 24B
56
- '46': 24I
57
- '47': 24T
58
- '48': 2AC
59
- '49': 2AC1
60
- '50': 2AE
61
- '51': 2AEHS
62
- '52': 2AMHS
63
- '53': 2AMN
64
- '54': 2ANE
65
- '55': 2ANHS
66
- '56': 2HS
67
- '57': 2PC
68
- '58': 2PC.
69
- '59': 2PE
70
- '60': 2PEHS
71
- '61': 2PME
72
- '62': 2PMHS
73
- '63': 2PMN
74
- '64': 2PNE
75
- '65': 2PNHS
76
- '66': 3AC
77
- '67': 3AC1
78
- '68': 3AMEHS
79
- '69': 3AMNHS
80
- '70': 3ANEHS
81
- '71': 3HS
82
- '72': 3PC
83
- '73': 3PMEHS
84
- '74': 3PMNHS
85
- '75': 3PNEHS
86
- '76': 3WMNE
87
- '77': 48
88
- '78': 4AC
89
- '79': 4PC
90
- '80': 4T
91
- '81': 58
92
- '82': 5DS
93
- '83': 6.3
94
- '84': 618
95
- '85': 7.3
96
- '86': 719
97
- '87': 8
98
- '88': 8.3
99
- '89': 820
100
- '90': 9.3
101
- '91': 921
102
- '92': A11
103
- '93': A12
104
- '94': A13
105
- '95': A14
106
- '96': A15
107
- '97': A21
108
- '98': A22
109
- '99': A23
110
- '100': A24
111
- '101': A25
112
- '102': A26
113
- '103': A31
114
- '104': A32
115
- '105': A33
116
- '106': A35
117
- '107': A37
118
- '108': A38
119
- '109': A39
120
- '110': A40
121
- '111': A41
122
- '112': A41.
123
- '113': A42
124
- '114': A43
125
- '115': A44
126
- '116': A45
127
- '117': A45.
128
- '118': A46
129
- '119': A47
130
- '120': A48
131
- '121': A49
132
- '122': A50
133
- '123': A51
134
- '124': A52
135
- '125': A53
136
- '126': A54
137
- '127': A55
138
- '128': A56
139
- '129': A57
140
- '130': A58
141
- '131': AMB
142
- '132': AT1
143
- '133': AT2
144
- '134': BHD
145
- '135': BMB
146
- '136': D5W
147
- '137': DL
148
- '138': DM1
149
- '139': DM2
150
- '140': DM3
151
- '141': DM4
152
- '142': HAD
153
- '143': HAV
154
- '144': HD
155
- '145': HS
156
- '146': JN
157
- '147': KE1
158
- '148': KE2
159
- '149': KU1
160
- '150': KU2
161
- '151': MF
162
- '152': MNE
163
- '153': NF
164
- '154': NF.
165
- '155': NFF
166
- '156': NSS
167
- '157': OP
168
- '158': OP1
169
- '159': OPD
170
- '160': OT
171
- '161': P11
172
- '162': P12
173
- '163': P13
174
- '164': P21
175
- '165': P22
176
- '166': P23
177
- '167': P24
178
- '168': P25
179
- '169': P26
180
- '170': P31
181
- '171': P32
182
- '172': P33
183
- '173': P34
184
- '174': P41
185
- '175': PC1
186
- '176': PC2
187
- '177': PC3
188
- '178': PF
189
- '179': PRN
190
- '180': PRNFEV
191
- '181': PRNNV
192
- '182': PRNคัน
193
- '183': PRNผื่น
194
- '184': Q12
195
- '185': Q24
196
- '186': Q4
197
- '187': Q6
198
- '188': Q8
199
- '189': RED
200
- '190': S
201
- '191': T
202
- '192': T11
203
- '193': T12
204
- '194': T13
205
- '195': T14
206
- '196': T20
207
- '197': T21
208
- '198': T22
209
- '199': T23
210
- '200': T24
211
- '201': T25
212
- '202': T26
213
- '203': T31
214
- '204': T32
215
- '205': T33
216
- '206': T34
217
- '207': T41
218
- '208': T7
219
- '209': TE
220
- '210': TEHS
221
- '211': THS
222
- '212': TM
223
- '213': TME
224
- '214': TMEHS
225
- '215': TMHS
226
- '216': TMN
227
- '217': TMNE
228
- '218': TMNEHS
229
- '219': TMNHS
230
- '220': TN
231
- '221': TNE
232
- '222': TNEHS
233
- '223': TNHS
234
- '224': TT
235
- '225': TT1
236
- '226': VES
237
- '227': WC
238
- '228': WCN
239
- '229': WD
240
- '230': WI
241
- '231': WIR
242
- '232': WM1
243
- '233': WO
244
- '234': WP
245
- '235': WPH
246
- '236': WPL
247
- '237': WS
248
- '238': WS2
249
- '239': WS3
250
- '240': WSB
251
- '241': WV
252
- '242': Z
253
- '243': t10.30
254
- '244': t630
255
- '245': t730
256
- '246': t8.30
257
- '247': t9.30
258
- '248': tt10
259
- '249': tt11
260
- '250': tt12
261
- '251': tt17
262
- '252': tt18
263
- '253': tt19
264
- '254': tt21
265
- '255': tt22
266
- '256': tt23
267
- '257': tt24
268
- '258': tt5
269
- '259': tt6
270
- '260': tt8
271
- '261': tt9
272
  splits:
273
  - name: train
274
  num_bytes: 17024
 
1
  ---
2
+ language:
3
+ - th
4
  dataset_info:
5
  features:
6
  - name: text
 
8
  - name: label
9
  dtype:
10
  class_label:
11
+ names:
12
+ '0': 0.5AE
13
+ '1': 0.5HS2
14
+ '2': 0.5HS3
15
+ '3': 0.5PE
16
+ '4': 0.5PN
17
+ '5': 0.5SSU
18
+ '6': 0
19
+ '7': 1.5SSU
20
+ '8': 10
21
+ '9': 10.3
22
+ '10': 1022
23
+ '11': 11
24
+ '12': 11.3
25
+ '13': 1123
26
+ '14': 11AE
27
+ '15': 11AN
28
+ '16': 11PE
29
+ '17': 11PN
30
+ '18': 12
31
+ '19': 12.3
32
+ '20': 1224
33
+ '21': 12T
34
+ '22': 15min
35
+ '23': 18.3
36
+ '24': 19.3
37
+ '25': 1AC
38
+ '26': 1AC1
39
+ '27': 1AE
40
+ '28': 1AN
41
+ '29': 1HR
42
+ '30': 1HS
43
+ '31': 1HS2
44
+ '32': 1HS3
45
+ '33': 1KP
46
+ '34': 1PC
47
+ '35': 1PE
48
+ '36': 1PN
49
+ '37': 1PNE
50
+ '38': 1SSU
51
+ '39': 1WM
52
+ '40': 20.3
53
+ '41': 21.3
54
+ '42': 22.3
55
+ '43': 23.3
56
+ '44': 24
57
+ '45': 24B
58
+ '46': 24I
59
+ '47': 24T
60
+ '48': 2AC
61
+ '49': 2AC1
62
+ '50': 2AE
63
+ '51': 2AEHS
64
+ '52': 2AMHS
65
+ '53': 2AMN
66
+ '54': 2ANE
67
+ '55': 2ANHS
68
+ '56': 2HS
69
+ '57': 2PC
70
+ '58': 2PC.
71
+ '59': 2PE
72
+ '60': 2PEHS
73
+ '61': 2PME
74
+ '62': 2PMHS
75
+ '63': 2PMN
76
+ '64': 2PNE
77
+ '65': 2PNHS
78
+ '66': 3AC
79
+ '67': 3AC1
80
+ '68': 3AMEHS
81
+ '69': 3AMNHS
82
+ '70': 3ANEHS
83
+ '71': 3HS
84
+ '72': 3PC
85
+ '73': 3PMEHS
86
+ '74': 3PMNHS
87
+ '75': 3PNEHS
88
+ '76': 3WMNE
89
+ '77': 48
90
+ '78': 4AC
91
+ '79': 4PC
92
+ '80': 4T
93
+ '81': 58
94
+ '82': 5DS
95
+ '83': 6.3
96
+ '84': 618
97
+ '85': 7.3
98
+ '86': 719
99
+ '87': 8
100
+ '88': 8.3
101
+ '89': 820
102
+ '90': 9.3
103
+ '91': 921
104
+ '92': A11
105
+ '93': A12
106
+ '94': A13
107
+ '95': A14
108
+ '96': A15
109
+ '97': A21
110
+ '98': A22
111
+ '99': A23
112
+ '100': A24
113
+ '101': A25
114
+ '102': A26
115
+ '103': A31
116
+ '104': A32
117
+ '105': A33
118
+ '106': A35
119
+ '107': A37
120
+ '108': A38
121
+ '109': A39
122
+ '110': A40
123
+ '111': A41
124
+ '112': A41.
125
+ '113': A42
126
+ '114': A43
127
+ '115': A44
128
+ '116': A45
129
+ '117': A45.
130
+ '118': A46
131
+ '119': A47
132
+ '120': A48
133
+ '121': A49
134
+ '122': A50
135
+ '123': A51
136
+ '124': A52
137
+ '125': A53
138
+ '126': A54
139
+ '127': A55
140
+ '128': A56
141
+ '129': A57
142
+ '130': A58
143
+ '131': AMB
144
+ '132': AT1
145
+ '133': AT2
146
+ '134': BHD
147
+ '135': BMB
148
+ '136': D5W
149
+ '137': DL
150
+ '138': DM1
151
+ '139': DM2
152
+ '140': DM3
153
+ '141': DM4
154
+ '142': HAD
155
+ '143': HAV
156
+ '144': HD
157
+ '145': HS
158
+ '146': JN
159
+ '147': KE1
160
+ '148': KE2
161
+ '149': KU1
162
+ '150': KU2
163
+ '151': MF
164
+ '152': MNE
165
+ '153': NF
166
+ '154': NF.
167
+ '155': NFF
168
+ '156': NSS
169
+ '157': OP
170
+ '158': OP1
171
+ '159': OPD
172
+ '160': OT
173
+ '161': P11
174
+ '162': P12
175
+ '163': P13
176
+ '164': P21
177
+ '165': P22
178
+ '166': P23
179
+ '167': P24
180
+ '168': P25
181
+ '169': P26
182
+ '170': P31
183
+ '171': P32
184
+ '172': P33
185
+ '173': P34
186
+ '174': P41
187
+ '175': PC1
188
+ '176': PC2
189
+ '177': PC3
190
+ '178': PF
191
+ '179': PRN
192
+ '180': PRNFEV
193
+ '181': PRNNV
194
+ '182': PRNคัน
195
+ '183': PRNผื่น
196
+ '184': Q12
197
+ '185': Q24
198
+ '186': Q4
199
+ '187': Q6
200
+ '188': Q8
201
+ '189': RED
202
+ '190': S
203
+ '191': T
204
+ '192': T11
205
+ '193': T12
206
+ '194': T13
207
+ '195': T14
208
+ '196': T20
209
+ '197': T21
210
+ '198': T22
211
+ '199': T23
212
+ '200': T24
213
+ '201': T25
214
+ '202': T26
215
+ '203': T31
216
+ '204': T32
217
+ '205': T33
218
+ '206': T34
219
+ '207': T41
220
+ '208': T7
221
+ '209': TE
222
+ '210': TEHS
223
+ '211': THS
224
+ '212': TM
225
+ '213': TME
226
+ '214': TMEHS
227
+ '215': TMHS
228
+ '216': TMN
229
+ '217': TMNE
230
+ '218': TMNEHS
231
+ '219': TMNHS
232
+ '220': TN
233
+ '221': TNE
234
+ '222': TNEHS
235
+ '223': TNHS
236
+ '224': TT
237
+ '225': TT1
238
+ '226': VES
239
+ '227': WC
240
+ '228': WCN
241
+ '229': WD
242
+ '230': WI
243
+ '231': WIR
244
+ '232': WM1
245
+ '233': WO
246
+ '234': WP
247
+ '235': WPH
248
+ '236': WPL
249
+ '237': WS
250
+ '238': WS2
251
+ '239': WS3
252
+ '240': WSB
253
+ '241': WV
254
+ '242': Z
255
+ '243': t10.30
256
+ '244': t630
257
+ '245': t730
258
+ '246': t8.30
259
+ '247': t9.30
260
+ '248': tt10
261
+ '249': tt11
262
+ '250': tt12
263
+ '251': tt17
264
+ '252': tt18
265
+ '253': tt19
266
+ '254': tt21
267
+ '255': tt22
268
+ '256': tt23
269
+ '257': tt24
270
+ '258': tt5
271
+ '259': tt6
272
+ '260': tt8
273
+ '261': tt9
274
  splits:
275
  - name: train
276
  num_bytes: 17024