Hugging Face's logo

Datasets:
sasha
/
prof_images_blip__stabilityai-stable-diffusion-2

Modalities:
Image
Formats:
parquet
Size:
10K - 100K
Libraries:
Datasets
pandas
Dataset card Viewer Files Community
sasha HF staff commited on
Commit
fa66b59
•
1 Parent(s): 88423a9

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +452 -0
README.md ADDED
@@ -0,0 +1,452 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ dataset_info:
3
+ features:
4
+ - name: images
5
+ dtype: image
6
+ - name: embeddings
7
+ sequence: float32
8
+ splits:
9
+ - name: courier
10
+ num_bytes: 4257204.0
11
+ num_examples: 100
12
+ - name: aide
13
+ num_bytes: 3491678.0
14
+ num_examples: 100
15
+ - name: police_officer
16
+ num_bytes: 4252502.0
17
+ num_examples: 100
18
+ - name: purchasing_agent
19
+ num_bytes: 5285492.0
20
+ num_examples: 100
21
+ - name: metal_worker
22
+ num_bytes: 5097159.0
23
+ num_examples: 100
24
+ - name: financial_analyst
25
+ num_bytes: 5261660.0
26
+ num_examples: 100
27
+ - name: stocker
28
+ num_bytes: 5700830.0
29
+ num_examples: 100
30
+ - name: it_specialist
31
+ num_bytes: 5731031.0
32
+ num_examples: 100
33
+ - name: writer
34
+ num_bytes: 4309299.0
35
+ num_examples: 100
36
+ - name: accountant
37
+ num_bytes: 4689435.0
38
+ num_examples: 100
39
+ - name: coach
40
+ num_bytes: 4537870.0
41
+ num_examples: 100
42
+ - name: painter
43
+ num_bytes: 3686294.0
44
+ num_examples: 100
45
+ - name: real_estate_broker
46
+ num_bytes: 5241610.0
47
+ num_examples: 100
48
+ - name: truck_driver
49
+ num_bytes: 4955237.0
50
+ num_examples: 100
51
+ - name: data_entry_keyer
52
+ num_bytes: 6112746.0
53
+ num_examples: 100
54
+ - name: computer_support_specialist
55
+ num_bytes: 5187781.0
56
+ num_examples: 100
57
+ - name: cook
58
+ num_bytes: 3905039.0
59
+ num_examples: 100
60
+ - name: interior_designer
61
+ num_bytes: 4970044.0
62
+ num_examples: 100
63
+ - name: nutritionist
64
+ num_bytes: 4904269.0
65
+ num_examples: 100
66
+ - name: designer
67
+ num_bytes: 5618928.0
68
+ num_examples: 100
69
+ - name: maid
70
+ num_bytes: 3653112.0
71
+ num_examples: 100
72
+ - name: producer
73
+ num_bytes: 5532083.0
74
+ num_examples: 100
75
+ - name: executive_assistant
76
+ num_bytes: 5181631.0
77
+ num_examples: 100
78
+ - name: logistician
79
+ num_bytes: 5623819.0
80
+ num_examples: 100
81
+ - name: tractor_operator
82
+ num_bytes: 5566239.0
83
+ num_examples: 100
84
+ - name: doctor
85
+ num_bytes: 3922429.0
86
+ num_examples: 100
87
+ - name: inventory_clerk
88
+ num_bytes: 5675119.0
89
+ num_examples: 100
90
+ - name: sheet_metal_worker
91
+ num_bytes: 4932393.0
92
+ num_examples: 100
93
+ - name: groundskeeper
94
+ num_bytes: 5624913.0
95
+ num_examples: 100
96
+ - name: electrical_engineer
97
+ num_bytes: 5486843.0
98
+ num_examples: 100
99
+ - name: physical_therapist
100
+ num_bytes: 4416383.0
101
+ num_examples: 100
102
+ - name: insurance_agent
103
+ num_bytes: 4503029.0
104
+ num_examples: 100
105
+ - name: aerospace_engineer
106
+ num_bytes: 5005814.0
107
+ num_examples: 100
108
+ - name: psychologist
109
+ num_bytes: 4751138.0
110
+ num_examples: 100
111
+ - name: financial_advisor
112
+ num_bytes: 4616805.0
113
+ num_examples: 100
114
+ - name: printing_press_operator
115
+ num_bytes: 4885677.0
116
+ num_examples: 100
117
+ - name: architect
118
+ num_bytes: 4694972.0
119
+ num_examples: 100
120
+ - name: dental_hygienist
121
+ num_bytes: 4051984.0
122
+ num_examples: 100
123
+ - name: artist
124
+ num_bytes: 4093686.0
125
+ num_examples: 100
126
+ - name: office_worker
127
+ num_bytes: 4984173.0
128
+ num_examples: 100
129
+ - name: ceo
130
+ num_bytes: 4753603.0
131
+ num_examples: 100
132
+ - name: taxi_driver
133
+ num_bytes: 4839205.0
134
+ num_examples: 100
135
+ - name: librarian
136
+ num_bytes: 5209270.0
137
+ num_examples: 100
138
+ - name: author
139
+ num_bytes: 4326443.0
140
+ num_examples: 100
141
+ - name: plumber
142
+ num_bytes: 5004142.0
143
+ num_examples: 100
144
+ - name: construction_worker
145
+ num_bytes: 5173177.0
146
+ num_examples: 100
147
+ - name: clergy
148
+ num_bytes: 3852512.0
149
+ num_examples: 100
150
+ - name: electrician
151
+ num_bytes: 5239521.0
152
+ num_examples: 100
153
+ - name: jailer
154
+ num_bytes: 5032189.0
155
+ num_examples: 100
156
+ - name: credit_counselor
157
+ num_bytes: 4814481.0
158
+ num_examples: 100
159
+ - name: scientist
160
+ num_bytes: 4363783.0
161
+ num_examples: 100
162
+ - name: drywall_installer
163
+ num_bytes: 4174819.0
164
+ num_examples: 100
165
+ - name: school_bus_driver
166
+ num_bytes: 4998022.0
167
+ num_examples: 100
168
+ - name: dental_assistant
169
+ num_bytes: 4140296.0
170
+ num_examples: 100
171
+ - name: fitness_instructor
172
+ num_bytes: 4416504.0
173
+ num_examples: 100
174
+ - name: detective
175
+ num_bytes: 4583678.0
176
+ num_examples: 100
177
+ - name: hairdresser
178
+ num_bytes: 4463307.0
179
+ num_examples: 100
180
+ - name: welder
181
+ num_bytes: 4918374.0
182
+ num_examples: 100
183
+ - name: pharmacy_technician
184
+ num_bytes: 4661790.0
185
+ num_examples: 100
186
+ - name: compliance_officer
187
+ num_bytes: 4845349.0
188
+ num_examples: 100
189
+ - name: singer
190
+ num_bytes: 4638247.0
191
+ num_examples: 100
192
+ - name: tutor
193
+ num_bytes: 3678185.0
194
+ num_examples: 100
195
+ - name: language_pathologist
196
+ num_bytes: 5254361.0
197
+ num_examples: 100
198
+ - name: medical_records_specialist
199
+ num_bytes: 5634506.0
200
+ num_examples: 100
201
+ - name: sales_manager
202
+ num_bytes: 5056132.0
203
+ num_examples: 100
204
+ - name: industrial_engineer
205
+ num_bytes: 5172786.0
206
+ num_examples: 100
207
+ - name: manager
208
+ num_bytes: 4931846.0
209
+ num_examples: 100
210
+ - name: mechanic
211
+ num_bytes: 4613784.0
212
+ num_examples: 100
213
+ - name: postal_worker
214
+ num_bytes: 4441299.0
215
+ num_examples: 100
216
+ - name: computer_systems_analyst
217
+ num_bytes: 6079263.0
218
+ num_examples: 100
219
+ - name: salesperson
220
+ num_bytes: 5024667.0
221
+ num_examples: 100
222
+ - name: office_clerk
223
+ num_bytes: 4755914.0
224
+ num_examples: 100
225
+ - name: claims_appraiser
226
+ num_bytes: 4478395.0
227
+ num_examples: 100
228
+ - name: security_guard
229
+ num_bytes: 5230558.0
230
+ num_examples: 100
231
+ - name: interviewer
232
+ num_bytes: 4656965.0
233
+ num_examples: 100
234
+ - name: dispatcher
235
+ num_bytes: 5291584.0
236
+ num_examples: 100
237
+ - name: lawyer
238
+ num_bytes: 4277664.0
239
+ num_examples: 100
240
+ - name: marketing_manager
241
+ num_bytes: 5252505.0
242
+ num_examples: 100
243
+ - name: customer_service_representative
244
+ num_bytes: 4896010.0
245
+ num_examples: 100
246
+ - name: software_developer
247
+ num_bytes: 5547030.0
248
+ num_examples: 100
249
+ - name: mover
250
+ num_bytes: 4568118.0
251
+ num_examples: 100
252
+ - name: supervisor
253
+ num_bytes: 4923186.0
254
+ num_examples: 100
255
+ - name: paralegal
256
+ num_bytes: 4687033.0
257
+ num_examples: 100
258
+ - name: graphic_designer
259
+ num_bytes: 5759315.0
260
+ num_examples: 100
261
+ - name: dentist
262
+ num_bytes: 3970331.0
263
+ num_examples: 100
264
+ - name: roofer
265
+ num_bytes: 5495073.0
266
+ num_examples: 100
267
+ - name: public_relations_specialist
268
+ num_bytes: 5073442.0
269
+ num_examples: 100
270
+ - name: engineer
271
+ num_bytes: 4250666.0
272
+ num_examples: 100
273
+ - name: occupational_therapist
274
+ num_bytes: 3855692.0
275
+ num_examples: 100
276
+ - name: manicurist
277
+ num_bytes: 4064118.0
278
+ num_examples: 100
279
+ - name: cleaner
280
+ num_bytes: 5095971.0
281
+ num_examples: 100
282
+ - name: facilities_manager
283
+ num_bytes: 5247879.0
284
+ num_examples: 100
285
+ - name: repair_worker
286
+ num_bytes: 5113432.0
287
+ num_examples: 100
288
+ - name: cashier
289
+ num_bytes: 5215203.0
290
+ num_examples: 100
291
+ - name: baker
292
+ num_bytes: 4610706.0
293
+ num_examples: 100
294
+ - name: market_research_analyst
295
+ num_bytes: 5593811.0
296
+ num_examples: 100
297
+ - name: health_technician
298
+ num_bytes: 4477836.0
299
+ num_examples: 100
300
+ - name: veterinarian
301
+ num_bytes: 4197438.0
302
+ num_examples: 100
303
+ - name: underwriter
304
+ num_bytes: 4662113.0
305
+ num_examples: 100
306
+ - name: mechanical_engineer
307
+ num_bytes: 5722417.0
308
+ num_examples: 100
309
+ - name: janitor
310
+ num_bytes: 5390408.0
311
+ num_examples: 100
312
+ - name: pilot
313
+ num_bytes: 3829685.0
314
+ num_examples: 100
315
+ - name: therapist
316
+ num_bytes: 3859109.0
317
+ num_examples: 100
318
+ - name: director
319
+ num_bytes: 4096085.0
320
+ num_examples: 100
321
+ - name: wholesale_buyer
322
+ num_bytes: 6300854.0
323
+ num_examples: 100
324
+ - name: air_conditioning_installer
325
+ num_bytes: 5741602.0
326
+ num_examples: 100
327
+ - name: butcher
328
+ num_bytes: 5332426.0
329
+ num_examples: 100
330
+ - name: machinery_mechanic
331
+ num_bytes: 5057875.0
332
+ num_examples: 100
333
+ - name: event_planner
334
+ num_bytes: 5039870.0
335
+ num_examples: 100
336
+ - name: carpet_installer
337
+ num_bytes: 5903738.0
338
+ num_examples: 100
339
+ - name: musician
340
+ num_bytes: 4431405.0
341
+ num_examples: 100
342
+ - name: civil_engineer
343
+ num_bytes: 5463535.0
344
+ num_examples: 100
345
+ - name: farmer
346
+ num_bytes: 4772114.0
347
+ num_examples: 100
348
+ - name: financial_manager
349
+ num_bytes: 5187071.0
350
+ num_examples: 100
351
+ - name: childcare_worker
352
+ num_bytes: 4326077.0
353
+ num_examples: 100
354
+ - name: clerk
355
+ num_bytes: 4268877.0
356
+ num_examples: 100
357
+ - name: machinist
358
+ num_bytes: 4593820.0
359
+ num_examples: 100
360
+ - name: firefighter
361
+ num_bytes: 4414229.0
362
+ num_examples: 100
363
+ - name: photographer
364
+ num_bytes: 4056745.0
365
+ num_examples: 100
366
+ - name: file_clerk
367
+ num_bytes: 5925494.0
368
+ num_examples: 100
369
+ - name: bus_driver
370
+ num_bytes: 4714778.0
371
+ num_examples: 100
372
+ - name: fast_food_worker
373
+ num_bytes: 4778503.0
374
+ num_examples: 100
375
+ - name: bartender
376
+ num_bytes: 5407515.0
377
+ num_examples: 100
378
+ - name: computer_programmer
379
+ num_bytes: 5961791.0
380
+ num_examples: 100
381
+ - name: pharmacist
382
+ num_bytes: 5103862.0
383
+ num_examples: 100
384
+ - name: nursing_assistant
385
+ num_bytes: 3969985.0
386
+ num_examples: 100
387
+ - name: career_counselor
388
+ num_bytes: 4578703.0
389
+ num_examples: 100
390
+ - name: mental_health_counselor
391
+ num_bytes: 4915411.0
392
+ num_examples: 100
393
+ - name: network_administrator
394
+ num_bytes: 6576986.0
395
+ num_examples: 100
396
+ - name: teacher
397
+ num_bytes: 4112341.0
398
+ num_examples: 100
399
+ - name: dishwasher
400
+ num_bytes: 4582691.0
401
+ num_examples: 100
402
+ - name: teller
403
+ num_bytes: 4580341.0
404
+ num_examples: 100
405
+ - name: teaching_assistant
406
+ num_bytes: 4310141.0
407
+ num_examples: 100
408
+ - name: payroll_clerk
409
+ num_bytes: 5104922.0
410
+ num_examples: 100
411
+ - name: laboratory_technician
412
+ num_bytes: 4772940.0
413
+ num_examples: 100
414
+ - name: social_assistant
415
+ num_bytes: 4975461.0
416
+ num_examples: 100
417
+ - name: radiologic_technician
418
+ num_bytes: 4614401.0
419
+ num_examples: 100
420
+ - name: social_worker
421
+ num_bytes: 4143912.0
422
+ num_examples: 100
423
+ - name: nurse
424
+ num_bytes: 3251197.0
425
+ num_examples: 100
426
+ - name: receptionist
427
+ num_bytes: 4962877.0
428
+ num_examples: 100
429
+ - name: carpenter
430
+ num_bytes: 4367834.0
431
+ num_examples: 100
432
+ - name: correctional_officer
433
+ num_bytes: 5027428.0
434
+ num_examples: 100
435
+ - name: community_manager
436
+ num_bytes: 5327391.0
437
+ num_examples: 100
438
+ - name: massage_therapist
439
+ num_bytes: 4309573.0
440
+ num_examples: 100
441
+ - name: head_cook
442
+ num_bytes: 4488723.0
443
+ num_examples: 100
444
+ - name: plane_mechanic
445
+ num_bytes: 4650683.0
446
+ num_examples: 100
447
+ download_size: 729196101
448
+ dataset_size: 705285705.0
449
+ ---
450
+ # Dataset Card for "prof_images_blip__stabilityai-stable-diffusion-2"
451
+
452
+ [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)