Hugging Face's logo

Datasets:
codeShare
/
lora-training-data

Tags:
Not-For-All-Audiences
Dataset card Files
xet
 Community
1
codeShare commited on
Commit
5b3e5de
·
verified ·
1 Parent(s): 207aeb2

Upload make_txt_files_from_parquet.ipynb

Browse files
Files changed (1) hide show
  1. make_txt_files_from_parquet.ipynb +53 -956
make_txt_files_from_parquet.ipynb CHANGED
@@ -11,701 +11,30 @@
11
  },
12
  "language_info": {
13
  "name": "python"
14
- },
15
- "widgets": {
16
- "application/vnd.jupyter.widget-state+json": {
17
- "version_major": 2,
18
- "version_minor": 0,
19
- "state": {
20
- "09b8bd0773344d8e94af2e9270f0884d": {
21
- "model_module": "@jupyter-widgets/controls",
22
- "model_name": "HBoxModel",
23
- "model_module_version": "1.5.0",
24
- "state": {
25
- "_dom_classes": [],
26
- "_model_module": "@jupyter-widgets/controls",
27
- "_model_module_version": "1.5.0",
28
- "_model_name": "HBoxModel",
29
- "_view_count": null,
30
- "_view_module": "@jupyter-widgets/controls",
31
- "_view_module_version": "1.5.0",
32
- "_view_name": "HBoxView",
33
- "box_style": "",
34
- "children": [
35
- "IPY_MODEL_91122eb7d2e346f9ab3ab8b22008487a",
36
- "IPY_MODEL_33246e18d4ab4fbcba2cc04be53f327c",
37
- "IPY_MODEL_68f6628e57de479fb228165871e663ea"
38
- ],
39
- "layout": "IPY_MODEL_879bcdde36a5422b9b26f54d72dd2456"
40
- }
41
- },
42
- "91122eb7d2e346f9ab3ab8b22008487a": {
43
- "model_module": "@jupyter-widgets/controls",
44
- "model_name": "HTMLModel",
45
- "model_module_version": "1.5.0",
46
- "state": {
47
- "_dom_classes": [],
48
- "_model_module": "@jupyter-widgets/controls",
49
- "_model_module_version": "1.5.0",
50
- "_model_name": "HTMLModel",
51
- "_view_count": null,
52
- "_view_module": "@jupyter-widgets/controls",
53
- "_view_module_version": "1.5.0",
54
- "_view_name": "HTMLView",
55
- "description": "",
56
- "description_tooltip": null,
57
- "layout": "IPY_MODEL_684d7a9a10664bafac4a65097005d2e4",
58
- "placeholder": "​",
59
- "style": "IPY_MODEL_4a7329c5680a44efa835d840debf156a",
60
- "value": "characters/susie__deltarune_cb75f3bf.par(…): reconstructing file: 100%"
61
- }
62
- },
63
- "33246e18d4ab4fbcba2cc04be53f327c": {
64
- "model_module": "@jupyter-widgets/controls",
65
- "model_name": "FloatProgressModel",
66
- "model_module_version": "1.5.0",
67
- "state": {
68
- "_dom_classes": [],
69
- "_model_module": "@jupyter-widgets/controls",
70
- "_model_module_version": "1.5.0",
71
- "_model_name": "FloatProgressModel",
72
- "_view_count": null,
73
- "_view_module": "@jupyter-widgets/controls",
74
- "_view_module_version": "1.5.0",
75
- "_view_name": "ProgressView",
76
- "bar_style": "success",
77
- "description": "",
78
- "description_tooltip": null,
79
- "layout": "IPY_MODEL_3255a6c8c5604f44a1a5fe8b6f7624aa",
80
- "max": 6177999,
81
- "min": 0,
82
- "orientation": "horizontal",
83
- "style": "IPY_MODEL_60fc03e87991491ebe8b47605ee43699",
84
- "value": 6177999
85
- }
86
- },
87
- "68f6628e57de479fb228165871e663ea": {
88
- "model_module": "@jupyter-widgets/controls",
89
- "model_name": "HTMLModel",
90
- "model_module_version": "1.5.0",
91
- "state": {
92
- "_dom_classes": [],
93
- "_model_module": "@jupyter-widgets/controls",
94
- "_model_module_version": "1.5.0",
95
- "_model_name": "HTMLModel",
96
- "_view_count": null,
97
- "_view_module": "@jupyter-widgets/controls",
98
- "_view_module_version": "1.5.0",
99
- "_view_name": "HTMLView",
100
- "description": "",
101
- "description_tooltip": null,
102
- "layout": "IPY_MODEL_d33c25283fd24c31b9334fd15938dc78",
103
- "placeholder": "​",
104
- "style": "IPY_MODEL_61e1be68f1414a299bfb6ae26a9ee99b",
105
- "value": " 6.18MB / 6.18MB,  558kB/s  "
106
- }
107
- },
108
- "879bcdde36a5422b9b26f54d72dd2456": {
109
- "model_module": "@jupyter-widgets/base",
110
- "model_name": "LayoutModel",
111
- "model_module_version": "1.2.0",
112
- "state": {
113
- "_model_module": "@jupyter-widgets/base",
114
- "_model_module_version": "1.2.0",
115
- "_model_name": "LayoutModel",
116
- "_view_count": null,
117
- "_view_module": "@jupyter-widgets/base",
118
- "_view_module_version": "1.2.0",
119
- "_view_name": "LayoutView",
120
- "align_content": null,
121
- "align_items": null,
122
- "align_self": null,
123
- "border": null,
124
- "bottom": null,
125
- "display": null,
126
- "flex": null,
127
- "flex_flow": null,
128
- "grid_area": null,
129
- "grid_auto_columns": null,
130
- "grid_auto_flow": null,
131
- "grid_auto_rows": null,
132
- "grid_column": null,
133
- "grid_gap": null,
134
- "grid_row": null,
135
- "grid_template_areas": null,
136
- "grid_template_columns": null,
137
- "grid_template_rows": null,
138
- "height": null,
139
- "justify_content": null,
140
- "justify_items": null,
141
- "left": null,
142
- "margin": null,
143
- "max_height": null,
144
- "max_width": null,
145
- "min_height": null,
146
- "min_width": null,
147
- "object_fit": null,
148
- "object_position": null,
149
- "order": null,
150
- "overflow": null,
151
- "overflow_x": null,
152
- "overflow_y": null,
153
- "padding": null,
154
- "right": null,
155
- "top": null,
156
- "visibility": null,
157
- "width": null
158
- }
159
- },
160
- "684d7a9a10664bafac4a65097005d2e4": {
161
- "model_module": "@jupyter-widgets/base",
162
- "model_name": "LayoutModel",
163
- "model_module_version": "1.2.0",
164
- "state": {
165
- "_model_module": "@jupyter-widgets/base",
166
- "_model_module_version": "1.2.0",
167
- "_model_name": "LayoutModel",
168
- "_view_count": null,
169
- "_view_module": "@jupyter-widgets/base",
170
- "_view_module_version": "1.2.0",
171
- "_view_name": "LayoutView",
172
- "align_content": null,
173
- "align_items": null,
174
- "align_self": null,
175
- "border": null,
176
- "bottom": null,
177
- "display": null,
178
- "flex": null,
179
- "flex_flow": null,
180
- "grid_area": null,
181
- "grid_auto_columns": null,
182
- "grid_auto_flow": null,
183
- "grid_auto_rows": null,
184
- "grid_column": null,
185
- "grid_gap": null,
186
- "grid_row": null,
187
- "grid_template_areas": null,
188
- "grid_template_columns": null,
189
- "grid_template_rows": null,
190
- "height": null,
191
- "justify_content": null,
192
- "justify_items": null,
193
- "left": null,
194
- "margin": null,
195
- "max_height": null,
196
- "max_width": null,
197
- "min_height": null,
198
- "min_width": null,
199
- "object_fit": null,
200
- "object_position": null,
201
- "order": null,
202
- "overflow": null,
203
- "overflow_x": null,
204
- "overflow_y": null,
205
- "padding": null,
206
- "right": null,
207
- "top": null,
208
- "visibility": null,
209
- "width": null
210
- }
211
- },
212
- "4a7329c5680a44efa835d840debf156a": {
213
- "model_module": "@jupyter-widgets/controls",
214
- "model_name": "DescriptionStyleModel",
215
- "model_module_version": "1.5.0",
216
- "state": {
217
- "_model_module": "@jupyter-widgets/controls",
218
- "_model_module_version": "1.5.0",
219
- "_model_name": "DescriptionStyleModel",
220
- "_view_count": null,
221
- "_view_module": "@jupyter-widgets/base",
222
- "_view_module_version": "1.2.0",
223
- "_view_name": "StyleView",
224
- "description_width": ""
225
- }
226
- },
227
- "3255a6c8c5604f44a1a5fe8b6f7624aa": {
228
- "model_module": "@jupyter-widgets/base",
229
- "model_name": "LayoutModel",
230
- "model_module_version": "1.2.0",
231
- "state": {
232
- "_model_module": "@jupyter-widgets/base",
233
- "_model_module_version": "1.2.0",
234
- "_model_name": "LayoutModel",
235
- "_view_count": null,
236
- "_view_module": "@jupyter-widgets/base",
237
- "_view_module_version": "1.2.0",
238
- "_view_name": "LayoutView",
239
- "align_content": null,
240
- "align_items": null,
241
- "align_self": null,
242
- "border": null,
243
- "bottom": null,
244
- "display": null,
245
- "flex": null,
246
- "flex_flow": null,
247
- "grid_area": null,
248
- "grid_auto_columns": null,
249
- "grid_auto_flow": null,
250
- "grid_auto_rows": null,
251
- "grid_column": null,
252
- "grid_gap": null,
253
- "grid_row": null,
254
- "grid_template_areas": null,
255
- "grid_template_columns": null,
256
- "grid_template_rows": null,
257
- "height": null,
258
- "justify_content": null,
259
- "justify_items": null,
260
- "left": null,
261
- "margin": null,
262
- "max_height": null,
263
- "max_width": null,
264
- "min_height": null,
265
- "min_width": null,
266
- "object_fit": null,
267
- "object_position": null,
268
- "order": null,
269
- "overflow": null,
270
- "overflow_x": null,
271
- "overflow_y": null,
272
- "padding": null,
273
- "right": null,
274
- "top": null,
275
- "visibility": null,
276
- "width": null
277
- }
278
- },
279
- "60fc03e87991491ebe8b47605ee43699": {
280
- "model_module": "@jupyter-widgets/controls",
281
- "model_name": "ProgressStyleModel",
282
- "model_module_version": "1.5.0",
283
- "state": {
284
- "_model_module": "@jupyter-widgets/controls",
285
- "_model_module_version": "1.5.0",
286
- "_model_name": "ProgressStyleModel",
287
- "_view_count": null,
288
- "_view_module": "@jupyter-widgets/base",
289
- "_view_module_version": "1.2.0",
290
- "_view_name": "StyleView",
291
- "bar_color": null,
292
- "description_width": ""
293
- }
294
- },
295
- "d33c25283fd24c31b9334fd15938dc78": {
296
- "model_module": "@jupyter-widgets/base",
297
- "model_name": "LayoutModel",
298
- "model_module_version": "1.2.0",
299
- "state": {
300
- "_model_module": "@jupyter-widgets/base",
301
- "_model_module_version": "1.2.0",
302
- "_model_name": "LayoutModel",
303
- "_view_count": null,
304
- "_view_module": "@jupyter-widgets/base",
305
- "_view_module_version": "1.2.0",
306
- "_view_name": "LayoutView",
307
- "align_content": null,
308
- "align_items": null,
309
- "align_self": null,
310
- "border": null,
311
- "bottom": null,
312
- "display": null,
313
- "flex": null,
314
- "flex_flow": null,
315
- "grid_area": null,
316
- "grid_auto_columns": null,
317
- "grid_auto_flow": null,
318
- "grid_auto_rows": null,
319
- "grid_column": null,
320
- "grid_gap": null,
321
- "grid_row": null,
322
- "grid_template_areas": null,
323
- "grid_template_columns": null,
324
- "grid_template_rows": null,
325
- "height": null,
326
- "justify_content": null,
327
- "justify_items": null,
328
- "left": null,
329
- "margin": null,
330
- "max_height": null,
331
- "max_width": null,
332
- "min_height": null,
333
- "min_width": null,
334
- "object_fit": null,
335
- "object_position": null,
336
- "order": null,
337
- "overflow": null,
338
- "overflow_x": null,
339
- "overflow_y": null,
340
- "padding": null,
341
- "right": null,
342
- "top": null,
343
- "visibility": null,
344
- "width": null
345
- }
346
- },
347
- "61e1be68f1414a299bfb6ae26a9ee99b": {
348
- "model_module": "@jupyter-widgets/controls",
349
- "model_name": "DescriptionStyleModel",
350
- "model_module_version": "1.5.0",
351
- "state": {
352
- "_model_module": "@jupyter-widgets/controls",
353
- "_model_module_version": "1.5.0",
354
- "_model_name": "DescriptionStyleModel",
355
- "_view_count": null,
356
- "_view_module": "@jupyter-widgets/base",
357
- "_view_module_version": "1.2.0",
358
- "_view_name": "StyleView",
359
- "description_width": ""
360
- }
361
- },
362
- "97959b137e654313b2b887cf00c3dcd6": {
363
- "model_module": "@jupyter-widgets/controls",
364
- "model_name": "HBoxModel",
365
- "model_module_version": "1.5.0",
366
- "state": {
367
- "_dom_classes": [],
368
- "_model_module": "@jupyter-widgets/controls",
369
- "_model_module_version": "1.5.0",
370
- "_model_name": "HBoxModel",
371
- "_view_count": null,
372
- "_view_module": "@jupyter-widgets/controls",
373
- "_view_module_version": "1.5.0",
374
- "_view_name": "HBoxView",
375
- "box_style": "",
376
- "children": [
377
- "IPY_MODEL_f6dd6aedacae45929e3486fb62949453",
378
- "IPY_MODEL_03fc05e3434d466eb4056020e4c6645c",
379
- "IPY_MODEL_7f8762e36c7645f5870c0e511e264f2e"
380
- ],
381
- "layout": "IPY_MODEL_60d25245d6954008b9cc8d3dcfedfcf2"
382
- }
383
- },
384
- "f6dd6aedacae45929e3486fb62949453": {
385
- "model_module": "@jupyter-widgets/controls",
386
- "model_name": "HTMLModel",
387
- "model_module_version": "1.5.0",
388
- "state": {
389
- "_dom_classes": [],
390
- "_model_module": "@jupyter-widgets/controls",
391
- "_model_module_version": "1.5.0",
392
- "_model_name": "HTMLModel",
393
- "_view_count": null,
394
- "_view_module": "@jupyter-widgets/controls",
395
- "_view_module_version": "1.5.0",
396
- "_view_name": "HTMLView",
397
- "description": "",
398
- "description_tooltip": null,
399
- "layout": "IPY_MODEL_4627b89f82c5414782c5fa3954a20b27",
400
- "placeholder": "​",
401
- "style": "IPY_MODEL_33abeee4292143acb1c9a56da6631f2a",
402
- "value": "characters/susie__deltarune_cb75f3bf.par(…): downloading bytes: "
403
- }
404
- },
405
- "03fc05e3434d466eb4056020e4c6645c": {
406
- "model_module": "@jupyter-widgets/controls",
407
- "model_name": "FloatProgressModel",
408
- "model_module_version": "1.5.0",
409
- "state": {
410
- "_dom_classes": [],
411
- "_model_module": "@jupyter-widgets/controls",
412
- "_model_module_version": "1.5.0",
413
- "_model_name": "FloatProgressModel",
414
- "_view_count": null,
415
- "_view_module": "@jupyter-widgets/controls",
416
- "_view_module_version": "1.5.0",
417
- "_view_name": "ProgressView",
418
- "bar_style": "success",
419
- "description": "",
420
- "description_tooltip": null,
421
- "layout": "IPY_MODEL_89c253845948429aa12d778d7b8673a3",
422
- "max": 6177999,
423
- "min": 0,
424
- "orientation": "horizontal",
425
- "style": "IPY_MODEL_8ed0bbe03d334f5db47935a0bd33659b",
426
- "value": 6177184
427
- }
428
- },
429
- "7f8762e36c7645f5870c0e511e264f2e": {
430
- "model_module": "@jupyter-widgets/controls",
431
- "model_name": "HTMLModel",
432
- "model_module_version": "1.5.0",
433
- "state": {
434
- "_dom_classes": [],
435
- "_model_module": "@jupyter-widgets/controls",
436
- "_model_module_version": "1.5.0",
437
- "_model_name": "HTMLModel",
438
- "_view_count": null,
439
- "_view_module": "@jupyter-widgets/controls",
440
- "_view_module_version": "1.5.0",
441
- "_view_name": "HTMLView",
442
- "description": "",
443
- "description_tooltip": null,
444
- "layout": "IPY_MODEL_406399d20ff5419c885933f8ae26efbd",
445
- "placeholder": "​",
446
- "style": "IPY_MODEL_0bbfbdfbc92b4ef5a760ab1a60c3ed61",
447
- "value": " 6.18MB,  550kB/s  "
448
- }
449
- },
450
- "60d25245d6954008b9cc8d3dcfedfcf2": {
451
- "model_module": "@jupyter-widgets/base",
452
- "model_name": "LayoutModel",
453
- "model_module_version": "1.2.0",
454
- "state": {
455
- "_model_module": "@jupyter-widgets/base",
456
- "_model_module_version": "1.2.0",
457
- "_model_name": "LayoutModel",
458
- "_view_count": null,
459
- "_view_module": "@jupyter-widgets/base",
460
- "_view_module_version": "1.2.0",
461
- "_view_name": "LayoutView",
462
- "align_content": null,
463
- "align_items": null,
464
- "align_self": null,
465
- "border": null,
466
- "bottom": null,
467
- "display": null,
468
- "flex": null,
469
- "flex_flow": null,
470
- "grid_area": null,
471
- "grid_auto_columns": null,
472
- "grid_auto_flow": null,
473
- "grid_auto_rows": null,
474
- "grid_column": null,
475
- "grid_gap": null,
476
- "grid_row": null,
477
- "grid_template_areas": null,
478
- "grid_template_columns": null,
479
- "grid_template_rows": null,
480
- "height": null,
481
- "justify_content": null,
482
- "justify_items": null,
483
- "left": null,
484
- "margin": null,
485
- "max_height": null,
486
- "max_width": null,
487
- "min_height": null,
488
- "min_width": null,
489
- "object_fit": null,
490
- "object_position": null,
491
- "order": null,
492
- "overflow": null,
493
- "overflow_x": null,
494
- "overflow_y": null,
495
- "padding": null,
496
- "right": null,
497
- "top": null,
498
- "visibility": null,
499
- "width": null
500
- }
501
- },
502
- "4627b89f82c5414782c5fa3954a20b27": {
503
- "model_module": "@jupyter-widgets/base",
504
- "model_name": "LayoutModel",
505
- "model_module_version": "1.2.0",
506
- "state": {
507
- "_model_module": "@jupyter-widgets/base",
508
- "_model_module_version": "1.2.0",
509
- "_model_name": "LayoutModel",
510
- "_view_count": null,
511
- "_view_module": "@jupyter-widgets/base",
512
- "_view_module_version": "1.2.0",
513
- "_view_name": "LayoutView",
514
- "align_content": null,
515
- "align_items": null,
516
- "align_self": null,
517
- "border": null,
518
- "bottom": null,
519
- "display": null,
520
- "flex": null,
521
- "flex_flow": null,
522
- "grid_area": null,
523
- "grid_auto_columns": null,
524
- "grid_auto_flow": null,
525
- "grid_auto_rows": null,
526
- "grid_column": null,
527
- "grid_gap": null,
528
- "grid_row": null,
529
- "grid_template_areas": null,
530
- "grid_template_columns": null,
531
- "grid_template_rows": null,
532
- "height": null,
533
- "justify_content": null,
534
- "justify_items": null,
535
- "left": null,
536
- "margin": null,
537
- "max_height": null,
538
- "max_width": null,
539
- "min_height": null,
540
- "min_width": null,
541
- "object_fit": null,
542
- "object_position": null,
543
- "order": null,
544
- "overflow": null,
545
- "overflow_x": null,
546
- "overflow_y": null,
547
- "padding": null,
548
- "right": null,
549
- "top": null,
550
- "visibility": null,
551
- "width": null
552
- }
553
- },
554
- "33abeee4292143acb1c9a56da6631f2a": {
555
- "model_module": "@jupyter-widgets/controls",
556
- "model_name": "DescriptionStyleModel",
557
- "model_module_version": "1.5.0",
558
- "state": {
559
- "_model_module": "@jupyter-widgets/controls",
560
- "_model_module_version": "1.5.0",
561
- "_model_name": "DescriptionStyleModel",
562
- "_view_count": null,
563
- "_view_module": "@jupyter-widgets/base",
564
- "_view_module_version": "1.2.0",
565
- "_view_name": "StyleView",
566
- "description_width": ""
567
- }
568
- },
569
- "89c253845948429aa12d778d7b8673a3": {
570
- "model_module": "@jupyter-widgets/base",
571
- "model_name": "LayoutModel",
572
- "model_module_version": "1.2.0",
573
- "state": {
574
- "_model_module": "@jupyter-widgets/base",
575
- "_model_module_version": "1.2.0",
576
- "_model_name": "LayoutModel",
577
- "_view_count": null,
578
- "_view_module": "@jupyter-widgets/base",
579
- "_view_module_version": "1.2.0",
580
- "_view_name": "LayoutView",
581
- "align_content": null,
582
- "align_items": null,
583
- "align_self": null,
584
- "border": null,
585
- "bottom": null,
586
- "display": null,
587
- "flex": null,
588
- "flex_flow": null,
589
- "grid_area": null,
590
- "grid_auto_columns": null,
591
- "grid_auto_flow": null,
592
- "grid_auto_rows": null,
593
- "grid_column": null,
594
- "grid_gap": null,
595
- "grid_row": null,
596
- "grid_template_areas": null,
597
- "grid_template_columns": null,
598
- "grid_template_rows": null,
599
- "height": null,
600
- "justify_content": null,
601
- "justify_items": null,
602
- "left": null,
603
- "margin": null,
604
- "max_height": null,
605
- "max_width": null,
606
- "min_height": null,
607
- "min_width": null,
608
- "object_fit": null,
609
- "object_position": null,
610
- "order": null,
611
- "overflow": null,
612
- "overflow_x": null,
613
- "overflow_y": null,
614
- "padding": null,
615
- "right": null,
616
- "top": null,
617
- "visibility": null,
618
- "width": null
619
- }
620
- },
621
- "8ed0bbe03d334f5db47935a0bd33659b": {
622
- "model_module": "@jupyter-widgets/controls",
623
- "model_name": "ProgressStyleModel",
624
- "model_module_version": "1.5.0",
625
- "state": {
626
- "_model_module": "@jupyter-widgets/controls",
627
- "_model_module_version": "1.5.0",
628
- "_model_name": "ProgressStyleModel",
629
- "_view_count": null,
630
- "_view_module": "@jupyter-widgets/base",
631
- "_view_module_version": "1.2.0",
632
- "_view_name": "StyleView",
633
- "bar_color": null,
634
- "description_width": ""
635
- }
636
- },
637
- "406399d20ff5419c885933f8ae26efbd": {
638
- "model_module": "@jupyter-widgets/base",
639
- "model_name": "LayoutModel",
640
- "model_module_version": "1.2.0",
641
- "state": {
642
- "_model_module": "@jupyter-widgets/base",
643
- "_model_module_version": "1.2.0",
644
- "_model_name": "LayoutModel",
645
- "_view_count": null,
646
- "_view_module": "@jupyter-widgets/base",
647
- "_view_module_version": "1.2.0",
648
- "_view_name": "LayoutView",
649
- "align_content": null,
650
- "align_items": null,
651
- "align_self": null,
652
- "border": null,
653
- "bottom": null,
654
- "display": null,
655
- "flex": null,
656
- "flex_flow": null,
657
- "grid_area": null,
658
- "grid_auto_columns": null,
659
- "grid_auto_flow": null,
660
- "grid_auto_rows": null,
661
- "grid_column": null,
662
- "grid_gap": null,
663
- "grid_row": null,
664
- "grid_template_areas": null,
665
- "grid_template_columns": null,
666
- "grid_template_rows": null,
667
- "height": null,
668
- "justify_content": null,
669
- "justify_items": null,
670
- "left": null,
671
- "margin": null,
672
- "max_height": null,
673
- "max_width": null,
674
- "min_height": null,
675
- "min_width": null,
676
- "object_fit": null,
677
- "object_position": null,
678
- "order": null,
679
- "overflow": null,
680
- "overflow_x": null,
681
- "overflow_y": null,
682
- "padding": null,
683
- "right": null,
684
- "top": null,
685
- "visibility": null,
686
- "width": null
687
- }
688
- },
689
- "0bbfbdfbc92b4ef5a760ab1a60c3ed61": {
690
- "model_module": "@jupyter-widgets/controls",
691
- "model_name": "DescriptionStyleModel",
692
- "model_module_version": "1.5.0",
693
- "state": {
694
- "_model_module": "@jupyter-widgets/controls",
695
- "_model_module_version": "1.5.0",
696
- "_model_name": "DescriptionStyleModel",
697
- "_view_count": null,
698
- "_view_module": "@jupyter-widgets/base",
699
- "_view_module_version": "1.2.0",
700
- "_view_name": "StyleView",
701
- "description_width": ""
702
- }
703
- }
704
- }
705
- }
706
  }
707
  },
708
  "cells": [
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
709
  {
710
  "cell_type": "code",
711
  "metadata": {
@@ -908,124 +237,18 @@
908
  ]
909
  },
910
  {
911
- "cell_type": "code",
912
  "source": [
913
- "from google.colab import drive\n",
914
- "drive.mount('/content/drive')"
915
  ],
916
  "metadata": {
917
- "colab": {
918
- "base_uri": "https://localhost:8080/"
919
- },
920
- "id": "8zNty4Fjmz8J",
921
- "outputId": "4976483f-ea1c-4fd4-d9f1-1085b2a200bb"
922
- },
923
- "execution_count": 1,
924
- "outputs": [
925
- {
926
- "output_type": "stream",
927
- "name": "stdout",
928
- "text": [
929
- "Mounted at /content/drive\n"
930
- ]
931
- }
932
- ]
933
  },
934
  {
935
  "cell_type": "code",
936
- "metadata": {
937
- "colab": {
938
- "base_uri": "https://localhost:8080/"
939
- },
940
- "id": "7d85a4f2",
941
- "outputId": "0b364f39-cd33-4da4-ff96-51ed3776deb4"
942
- },
943
  "source": [
944
- "import os\n",
945
- "import glob\n",
946
- "import zipfile\n",
947
- "import pandas as pd\n",
948
- "\n",
949
- "# Define files to process\n",
950
- "files = [\n",
951
- " \"/content/drive/MyDrive/characters/ankha__animal_crossing_a9cffcf3.parquet\",\n",
952
- " \"/content/drive/MyDrive/characters/judy_hopps_cf43b250.parquet\",\n",
953
- " \"/content/drive/MyDrive/characters/midna_26a00f43.parquet\",\n",
954
- " \"/content/drive/MyDrive/characters/minnie_mouse_cff01df7.parquet\",\n",
955
- " \"/content/drive/MyDrive/characters/princess_zelda_e95b643a.parquet\"\n",
956
- "]\n",
957
- "\n",
958
- "output_dir = \"/content/extracted_descriptions\"\n",
959
- "os.makedirs(output_dir, exist_ok=True)\n",
960
- "\n",
961
- "txt_files_created = []\n",
962
- "\n",
963
- "for file_path in files:\n",
964
- " if not os.path.exists(file_path):\n",
965
- " print(f\"File not found: {file_path}\")\n",
966
- " continue\n",
967
- "\n",
968
- " # Get character name from file path\n",
969
- " base_name = os.path.basename(file_path).replace(\".parquet\", \"\")\n",
970
- " print(f\"Processing: {base_name}\")\n",
971
- "\n",
972
- " try:\n",
973
- " df = pd.read_parquet(file_path)\n",
974
- " except Exception as e:\n",
975
- " print(f\"Error reading {file_path}: {e}\")\n",
976
- " continue\n",
977
- "\n",
978
- " for col in df.columns:\n",
979
- " # Clean and get non-null, non-empty descriptions\n",
980
- " descriptions = df[col].dropna().astype(str).str.strip().tolist()\n",
981
- " descriptions = [d for d in descriptions if d]\n",
982
- "\n",
983
- " # Chunk into maximum of 300 descriptions\n",
984
- " chunk_size = 300\n",
985
- " for idx, i in enumerate(range(0, len(descriptions), chunk_size)):\n",
986
- " chunk = descriptions[i:i + chunk_size]\n",
987
- "\n",
988
- " # Format as {desc1|desc2|...}\n",
989
- " formatted_content = \"{\" + \"|\".join(chunk) + \"}\"\n",
990
- "\n",
991
- " # Save to a text file\n",
992
- " txt_filename = f\"{base_name}_{col}_part{idx+1}.txt\"\n",
993
- " txt_filepath = os.path.join(output_dir, txt_filename)\n",
994
- "\n",
995
- " with open(txt_filepath, \"w\", encoding=\"utf-8\") as f:\n",
996
- " f.write(formatted_content)\n",
997
  "\n",
998
- " txt_files_created.append(txt_filepath)\n",
999
- "\n",
1000
- "# Create zip file\n",
1001
- "zip_path = \"/content/descriptions_archive.zip\"\n",
1002
- "with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:\n",
1003
- " for file in txt_files_created:\n",
1004
- " zipf.write(file, os.path.basename(file))\n",
1005
- "\n",
1006
- "print(f\"\\nProcessing completed. Created {len(txt_files_created)} text files and zipped them into {zip_path}\")"
1007
- ],
1008
- "execution_count": null,
1009
- "outputs": [
1010
- {
1011
- "output_type": "stream",
1012
- "name": "stdout",
1013
- "text": [
1014
- "Processing: ankha__animal_crossing_a9cffcf3\n",
1015
- "Processing: judy_hopps_cf43b250\n",
1016
- "Processing: midna_26a00f43\n",
1017
- "Processing: minnie_mouse_cff01df7\n",
1018
- "Processing: princess_zelda_e95b643a\n",
1019
- "\n",
1020
- "Processing completed. Created 569 text files and zipped them into /content/descriptions_archive.zip\n"
1021
- ]
1022
- }
1023
- ]
1024
- },
1025
- {
1026
- "cell_type": "code",
1027
- "source": [
1028
- "#Remove bad symbols\n",
1029
  "import os\n",
1030
  "import re\n",
1031
  "import zipfile\n",
@@ -1087,167 +310,22 @@
1087
  "outputs": []
1088
  },
1089
  {
1090
- "cell_type": "code",
1091
- "metadata": {
1092
- "id": "74a571f0",
1093
- "outputId": "29d06c00-60bd-4aaf-a75e-68d8ff6f3274",
1094
- "colab": {
1095
- "base_uri": "https://localhost:8080/",
1096
- "height": 98,
1097
- "referenced_widgets": [
1098
- "09b8bd0773344d8e94af2e9270f0884d",
1099
- "91122eb7d2e346f9ab3ab8b22008487a",
1100
- "33246e18d4ab4fbcba2cc04be53f327c",
1101
- "68f6628e57de479fb228165871e663ea",
1102
- "879bcdde36a5422b9b26f54d72dd2456",
1103
- "684d7a9a10664bafac4a65097005d2e4",
1104
- "4a7329c5680a44efa835d840debf156a",
1105
- "3255a6c8c5604f44a1a5fe8b6f7624aa",
1106
- "60fc03e87991491ebe8b47605ee43699",
1107
- "d33c25283fd24c31b9334fd15938dc78",
1108
- "61e1be68f1414a299bfb6ae26a9ee99b",
1109
- "97959b137e654313b2b887cf00c3dcd6",
1110
- "f6dd6aedacae45929e3486fb62949453",
1111
- "03fc05e3434d466eb4056020e4c6645c",
1112
- "7f8762e36c7645f5870c0e511e264f2e",
1113
- "60d25245d6954008b9cc8d3dcfedfcf2",
1114
- "4627b89f82c5414782c5fa3954a20b27",
1115
- "33abeee4292143acb1c9a56da6631f2a",
1116
- "89c253845948429aa12d778d7b8673a3",
1117
- "8ed0bbe03d334f5db47935a0bd33659b",
1118
- "406399d20ff5419c885933f8ae26efbd",
1119
- "0bbfbdfbc92b4ef5a760ab1a60c3ed61"
1120
- ]
1121
- }
1122
- },
1123
  "source": [
1124
- "# Download the Hugging Face dataset\n",
1125
- "import os\n",
1126
- "from google.colab import userdata\n",
1127
- "from huggingface_hub import hf_hub_download\n",
1128
- "\n",
1129
- "try:\n",
1130
- " hf_token = userdata.get('HF_TOKEN')\n",
1131
- "except Exception as e:\n",
1132
- " hf_token = None\n",
1133
- " print(\"Warning: HF_TOKEN secret not found. Attempting download without token...\")\n",
1134
- "\n",
1135
- "# Download the specific parquet file from the repository\n",
1136
- "file_path = hf_hub_download(\n",
1137
- " repo_id=\"codeShare/e621-sections-split\",\n",
1138
- " filename=\"characters/susie__deltarune_cb75f3bf.parquet\",\n",
1139
- " repo_type=\"dataset\",\n",
1140
- " token=hf_token,\n",
1141
- " local_dir=\"/content\"\n",
1142
- ")\n",
1143
- "print(f\"Downloaded file to: {file_path}\")"
1144
  ],
1145
- "execution_count": null,
1146
- "outputs": [
1147
- {
1148
- "output_type": "display_data",
1149
- "data": {
1150
- "text/plain": [
1151
- "characters/susie__deltarune_cb75f3bf.par(…): reconstructing file: 0%| | 0.00B / 6.18MB "
1152
- ],
1153
- "application/vnd.jupyter.widget-view+json": {
1154
- "version_major": 2,
1155
- "version_minor": 0,
1156
- "model_id": "09b8bd0773344d8e94af2e9270f0884d"
1157
- }
1158
- },
1159
- "metadata": {}
1160
- },
1161
- {
1162
- "output_type": "display_data",
1163
- "data": {
1164
- "text/plain": [
1165
- "characters/susie__deltarune_cb75f3bf.par(…): downloading bytes: | 0.00B "
1166
- ],
1167
- "application/vnd.jupyter.widget-view+json": {
1168
- "version_major": 2,
1169
- "version_minor": 0,
1170
- "model_id": "97959b137e654313b2b887cf00c3dcd6"
1171
- }
1172
- },
1173
- "metadata": {}
1174
- },
1175
- {
1176
- "output_type": "stream",
1177
- "name": "stdout",
1178
- "text": [
1179
- "Downloaded file to: /content/characters/susie__deltarune_cb75f3bf.parquet\n"
1180
- ]
1181
- }
1182
- ]
1183
- },
1184
- {
1185
- "cell_type": "code",
1186
  "metadata": {
1187
- "id": "d7e7a3b0"
1188
- },
1189
- "source": [
1190
- "# Clean, format, chunk, and zip the Susie dataset\n",
1191
- "import re\n",
1192
- "import zipfile\n",
1193
- "import pandas as pd\n",
1194
- "\n",
1195
- "# Load downloaded parquet\n",
1196
- "df = pd.read_parquet(file_path)\n",
1197
- "\n",
1198
- "# Allowed pattern: a-zA-Z0-9, ., !, ?, |, _, ,, and space\n",
1199
- "allowed_pattern = re.compile(r'[^a-zA-Z0-9.!_?|,\\s]')\n",
1200
- "\n",
1201
- "susie_output_dir = \"/content/susie_processed_descriptions\"\n",
1202
- "os.makedirs(susie_output_dir, exist_ok=True)\n",
1203
- "txt_files_created = []\n",
1204
- "\n",
1205
- "base_name = \"susie__deltarune_cb75f3bf\"\n",
1206
- "\n",
1207
- "for col in df.columns:\n",
1208
- " # Clean values and filter nulls/empties\n",
1209
- " descriptions = df[col].dropna().astype(str).str.strip().tolist()\n",
1210
- " cleaned_descriptions = []\n",
1211
- " for d in descriptions:\n",
1212
- " cleaned = allowed_pattern.sub('', d).strip()\n",
1213
- " if cleaned:\n",
1214
- " cleaned_descriptions.append(cleaned)\n",
1215
- "\n",
1216
- " # Split into chunks of 300\n",
1217
- " chunk_size = 300\n",
1218
- " for idx, i in enumerate(range(0, len(cleaned_descriptions), chunk_size)):\n",
1219
- " chunk = cleaned_descriptions[i:i + chunk_size]\n",
1220
- "\n",
1221
- " # Format as {desc1|desc2|...}\n",
1222
- " formatted_content = \"{\" + \"|\".join(chunk) + \"}\"\n",
1223
- "\n",
1224
- " txt_filename = f\"{base_name}_{col}_part{idx+1}.txt\"\n",
1225
- " txt_filepath = os.path.join(susie_output_dir, txt_filename)\n",
1226
- "\n",
1227
- " with open(txt_filepath, \"w\", encoding=\"utf-8\") as f:\n",
1228
- " f.write(formatted_content)\n",
1229
- "\n",
1230
- " txt_files_created.append(txt_filepath)\n",
1231
- "\n",
1232
- "# Zip the processed files to /content/\n",
1233
- "susie_zip_path = \"/content/susie_processed_archive.zip\"\n",
1234
- "with zipfile.ZipFile(susie_zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:\n",
1235
- " for file in txt_files_created:\n",
1236
- " zipf.write(file, os.path.basename(file))\n",
1237
- "\n",
1238
- "print(f\"Processing complete! Saved {len(txt_files_created)} text files to {susie_zip_path}\")"
1239
- ],
1240
- "execution_count": null,
1241
- "outputs": []
1242
  },
1243
  {
1244
  "cell_type": "code",
1245
  "metadata": {
1246
- "id": "ff7cb87e",
1247
- "outputId": "f84071d5-fe27-4238-be22-0ff0c962f5a9",
1248
  "colab": {
1249
  "base_uri": "https://localhost:8080/"
1250
- }
 
 
1251
  },
1252
  "source": [
1253
  "import os\n",
@@ -1339,7 +417,7 @@
1339
  "\n",
1340
  "print(\"\\nAll characters processed successfully!\")"
1341
  ],
1342
- "execution_count": null,
1343
  "outputs": [
1344
  {
1345
  "output_type": "stream",
@@ -1351,7 +429,26 @@
1351
  "Created and saved to Drive: /content/drive/MyDrive/characters/coco_bandicoot.zip (42 text files)\n",
1352
  "Processing: holo__spice_and_wolf\n",
1353
  "Created and saved to Drive: /content/drive/MyDrive/characters/holo__spice_and_wolf.zip (5 text files)\n",
1354
- "Processing: loona__helluva_boss\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1355
  ]
1356
  }
1357
  ]
 
11
  },
12
  "language_info": {
13
  "name": "python"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14
  }
15
  },
16
  "cells": [
17
+ {
18
+ "cell_type": "code",
19
+ "source": [
20
+ "from google.colab import drive\n",
21
+ "drive.mount('/content/drive')"
22
+ ],
23
+ "metadata": {
24
+ "id": "8zNty4Fjmz8J"
25
+ },
26
+ "execution_count": null,
27
+ "outputs": []
28
+ },
29
+ {
30
+ "cell_type": "markdown",
31
+ "source": [
32
+ "# Inspect parquet"
33
+ ],
34
+ "metadata": {
35
+ "id": "CH6oAzL6q5h7"
36
+ }
37
+ },
38
  {
39
  "cell_type": "code",
40
  "metadata": {
 
237
  ]
238
  },
239
  {
240
+ "cell_type": "markdown",
241
  "source": [
242
+ "# Remove bad symbols from text"
 
243
  ],
244
  "metadata": {
245
+ "id": "FGBYzw4CrFBa"
246
+ }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
247
  },
248
  {
249
  "cell_type": "code",
 
 
 
 
 
 
 
250
  "source": [
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
251
  "\n",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
252
  "import os\n",
253
  "import re\n",
254
  "import zipfile\n",
 
310
  "outputs": []
311
  },
312
  {
313
+ "cell_type": "markdown",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
314
  "source": [
315
+ "# Make txt_files_from_parquets\n"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
316
  ],
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
317
  "metadata": {
318
+ "id": "LRvZyfv3qop2"
319
+ }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
320
  },
321
  {
322
  "cell_type": "code",
323
  "metadata": {
 
 
324
  "colab": {
325
  "base_uri": "https://localhost:8080/"
326
+ },
327
+ "id": "ff7cb87e",
328
+ "outputId": "f84071d5-fe27-4238-be22-0ff0c962f5a9"
329
  },
330
  "source": [
331
  "import os\n",
 
417
  "\n",
418
  "print(\"\\nAll characters processed successfully!\")"
419
  ],
420
+ "execution_count": 2,
421
  "outputs": [
422
  {
423
  "output_type": "stream",
 
429
  "Created and saved to Drive: /content/drive/MyDrive/characters/coco_bandicoot.zip (42 text files)\n",
430
  "Processing: holo__spice_and_wolf\n",
431
  "Created and saved to Drive: /content/drive/MyDrive/characters/holo__spice_and_wolf.zip (5 text files)\n",
432
+ "Processing: loona__helluva_boss\n",
433
+ "Created and saved to Drive: /content/drive/MyDrive/characters/loona__helluva_boss.zip (68 text files)\n",
434
+ "Processing: mrs__katswell\n",
435
+ "Created and saved to Drive: /content/drive/MyDrive/characters/mrs__katswell.zip (18 text files)\n",
436
+ "Processing: nanachi\n",
437
+ "Created and saved to Drive: /content/drive/MyDrive/characters/nanachi.zip (5 text files)\n",
438
+ "Processing: nicole_watterson\n",
439
+ "Created and saved to Drive: /content/drive/MyDrive/characters/nicole_watterson.zip (35 text files)\n",
440
+ "Processing: rumi_usagiyama\n",
441
+ "Created and saved to Drive: /content/drive/MyDrive/characters/rumi_usagiyama.zip (8 text files)\n",
442
+ "Processing: samus_aran\n",
443
+ "Created and saved to Drive: /content/drive/MyDrive/characters/samus_aran.zip (11 text files)\n",
444
+ "Processing: shantae\n",
445
+ "Created and saved to Drive: /content/drive/MyDrive/characters/shantae.zip (10 text files)\n",
446
+ "Processing: sybil__pseudoregalia\n",
447
+ "Created and saved to Drive: /content/drive/MyDrive/characters/sybil__pseudoregalia.zip (5 text files)\n",
448
+ "Processing: tawna_bandicoot\n",
449
+ "Created and saved to Drive: /content/drive/MyDrive/characters/tawna_bandicoot.zip (37 text files)\n",
450
+ "\n",
451
+ "All characters processed successfully!\n"
452
  ]
453
  }
454
  ]