File size: 21,878 Bytes
e0ce9da
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6772214
233b3e5
5b8e1c5
e0ce9da
 
 
5b8e1c5
 
e0ce9da
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
48d18d9
e0ce9da
 
 
 
 
 
 
 
233b3e5
e0ce9da
 
 
 
 
 
 
 
093dabc
e0ce9da
 
 
 
 
 
 
 
89cb0cd
e0ce9da
 
 
 
 
 
 
 
a067486
e0ce9da
 
 
 
 
 
 
 
d18e04e
e0ce9da
 
 
 
 
 
 
 
233b3e5
e0ce9da
 
 
 
 
 
 
 
1ba7ab7
e0ce9da
 
 
 
 
 
 
 
233b3e5
e0ce9da
 
 
 
 
 
 
 
a067486
e0ce9da
 
 
 
 
 
 
 
d18e04e
e0ce9da
 
 
 
 
 
 
 
4b21f51
e0ce9da
 
 
 
 
 
 
 
48d18d9
e0ce9da
 
 
 
 
 
 
 
233b3e5
e0ce9da
 
 
 
 
 
 
 
48d18d9
e0ce9da
 
 
 
 
 
 
 
d18e04e
e0ce9da
 
 
 
 
 
 
 
093dabc
e0ce9da
 
 
 
 
 
 
 
659328e
e0ce9da
 
 
 
 
 
 
 
233b3e5
e0ce9da
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
---
license: other
base_model: "stabilityai/stable-diffusion-3.5-medium"
tags:
  - sd3
  - sd3-diffusers
  - text-to-image
  - diffusers
  - simpletuner
  - not-for-all-audiences
  - lora
  - template:sd-lora
  - lycoris
inference: true
widget:
- text: 'unconditional (blank prompt)'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_0_0.png
- text: 'Alien planet, strange rock formations, glowing plants, bizarre creatures, surreal atmosphere'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_1_0.png
- text: 'Alien marketplace, bizarre creatures, exotic goods, vibrant colors, otherworldly atmosphere'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_2_0.png
- text: 'Child holding a balloon, happy expression, colorful balloons, sunny day, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_3_0.png
- text: 'a 4-panel comic strip showing an orange cat saying the words ''HELP'' and ''LASAGNA'''
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_4_0.png
- text: 'a hand is holding a comic book with a cover that reads ''The Adventures of Superhero'''
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_5_0.png
- text: 'Underground cave filled with crystals, glowing lights, reflective surfaces, fantasy environment, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_6_0.png
- text: 'Bustling cyberpunk bazaar, vendors, neon signs, advanced tech, crowded, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_7_0.png
- text: 'Cyberpunk hacker in a dark room, neon glow, multiple screens, intense focus, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_8_0.png
- text: 'a cybernetic anne of green gables with neural implant and bio mech augmentations'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_9_0.png
- text: 'Post-apocalyptic cityscape, ruined buildings, overgrown vegetation, dark and gritty, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_10_0.png
- text: 'Magical castle in a lush forest, glowing windows, fantasy architecture, high resolution, detailed textures'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_11_0.png
- text: 'Ruins of an ancient temple in an enchanted forest, glowing runes, mystical creatures, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_12_0.png
- text: 'Mystical forest, glowing plants, fairies, magical creatures, fantasy art, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_13_0.png
- text: 'Magical garden with glowing flowers, fairies, serene atmosphere, detailed plants, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_14_0.png
- text: 'Whimsical garden filled with fairies, magical plants, sparkling lights, serene atmosphere, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_15_0.png
- text: 'Majestic dragon soaring through the sky, detailed scales, dynamic pose, fantasy art, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_16_0.png
- text: 'Fantasy world, floating islands in the sky, waterfalls, lush vegetation, detailed landscape, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_17_0.png
- text: 'Futuristic city skyline at night, neon lights, cyberpunk style, high contrast, sharp focus'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_18_0.png
- text: 'Space battle scene, starships fighting, laser beams, explosions, cosmic background'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_19_0.png
- text: 'Abandoned fairground at night, eerie rides, ghostly figures, fog, dark atmosphere, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_20_0.png
- text: 'Spooky haunted mansion on a hill, dark and eerie, glowing windows, ghostly atmosphere, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_21_0.png
- text: 'a hardcover physics textbook that is called PHYSICS FOR DUMMIES'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_22_0.png
- text: 'Epic medieval battle, knights in armor, dynamic action, detailed landscape, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_23_0.png
- text: 'Bustling medieval market with merchants, knights, and jesters, vibrant colors, detailed'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_24_0.png
- text: 'Cozy medieval tavern, warm firelight, adventurers drinking, detailed interior, rustic atmosphere'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_25_0.png
- text: 'Futuristic city skyline at night, neon lights, cyberpunk style, high contrast, sharp focus'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_26_0.png
- text: 'Forest with neon-lit trees, glowing plants, bioluminescence, surreal atmosphere, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_27_0.png
- text: 'Bright neon sign in a busy city street, ''Open 24 Hours'', bold typography, glowing lights'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_28_0.png
- text: 'Vibrant neon sign, ''Bar'', bold typography, dark background, glowing lights, detailed design'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_29_0.png
- text: 'Pirate ship on the high seas, stormy weather, detailed sails, dramatic waves, photorealistic'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_30_0.png
- text: 'Pirate discovering a treasure chest, detailed gold coins, tropical island, dramatic lighting'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_31_0.png
- text: 'a photograph of a woman experiencing a psychedelic trip. trippy, 8k, uhd, fractal'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_32_0.png
- text: 'Cozy cafe on a rainy day, people sipping coffee, warm lights, reflections on wet pavement, photorealistic'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_33_0.png
- text: '1980s arcade, neon lights, vintage game machines, kids playing, vibrant colors, nostalgic atmosphere'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_34_0.png
- text: '1980s game room with vintage arcade machines, neon lights, vibrant colors, nostalgic feel'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_35_0.png
- text: 'Robot blacksmith forging metal, sparks flying, detailed workshop, futuristic and medieval blend'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_36_0.png
- text: 'Sleek robot performing a dance, futuristic theater, holographic effects, detailed, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_37_0.png
- text: 'High-tech factory where robots are assembled, detailed machinery, futuristic setting, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_38_0.png
- text: 'Garden tended by robots, mechanical plants, colorful flowers, futuristic setting, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_39_0.png
- text: 'Cute robotic pet, futuristic home, sleek design, detailed features, friendly and animated'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_40_0.png
- text: 'cctv trail camera night time security picture of a wendigo in the woods'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_41_0.png
- text: 'Astronaut exploring an alien planet, detailed landscape, futuristic suit, cosmic background'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_42_0.png
- text: 'Futuristic space station orbiting a distant exoplanet, sleek design, detailed structures, cosmic backdrop'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_43_0.png
- text: 'a person holding a sign that reads ''SOON'''
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_44_0.png
- text: 'Steampunk airship in the sky, intricate design, Victorian aesthetics, dynamic scene, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_45_0.png
- text: 'Steampunk inventor in a workshop, intricate gadgets, Victorian attire, mechanical arm, goggles'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_46_0.png
- text: 'Stormy ocean with towering waves, dramatic skies, detailed water, intense atmosphere, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_47_0.png
- text: 'Dramatic stormy sea, lighthouse in the distance, lightning striking, dark clouds, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_48_0.png
- text: 'Graffiti artist creating a mural, vibrant colors, urban setting, dynamic action, high resolution'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_49_0.png
- text: 'Urban alleyway filled with vibrant graffiti art, tags and murals, realistic textures'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_50_0.png
- text: 'Urban street sign, ''Main Street'', bold typography, realistic textures, weathered look'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_51_0.png
- text: 'Classic car show with vintage vehicles, vibrant colors, nostalgic atmosphere, high detail'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_52_0.png
- text: 'Retro diner sign, ''Joe''s Diner'', classic 1950s design, neon lights, weathered look'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_53_0.png
- text: 'Vintage store sign with elaborate typography, ''Antique Shop'', hand-painted, weathered look'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_54_0.png
- text: 'A photo-realistic image of a cat'
  parameters:
    negative_prompt: 'ugly, cropped, blurry, low-quality, mediocre average'
  output:
    url: ./assets/image_55_0.png
---

# sd35m-photo-clip_value-shift3

This is a LyCORIS adapter derived from [stabilityai/stable-diffusion-3.5-medium](https://huggingface.co/stabilityai/stable-diffusion-3.5-medium).


The main validation prompt used during training was:
```
A photo-realistic image of a cat
```


## Validation settings
- CFG: `6.0`
- CFG Rescale: `0.0`
- Steps: `30`
- Sampler: `FlowMatchEulerDiscreteScheduler`
- Seed: `42`
- Resolution: `1024x1024`
- Skip-layer guidance: 

Note: The validation settings are not necessarily the same as the [training settings](#training-settings).

You can find some example images in the following gallery:


<Gallery />

The text encoder **was not** trained.
You may reuse the base model text encoder for inference.


## Training settings

- Training epochs: 2
- Training steps: 322000
- Learning rate: 5e-05
  - Learning rate schedule: constant
  - Warmup steps: 500
- Max grad norm: 1.0
- Effective batch size: 12
  - Micro-batch size: 4
  - Gradient accumulation steps: 1
  - Number of GPUs: 3
- Gradient checkpointing: True
- Prediction type: flow-matching (extra parameters=['shift=3.0'])
- Optimizer: bnb-adamw8bit
- Trainable parameter precision: Pure BF16
- Caption dropout probability: 10.0%


### LyCORIS Config:
```json
{
    "bypass_mode": true,
    "algo": "lokr",
    "multiplier": 1.0,
    "full_matrix": true,
    "linear_dim": 10000,
    "linear_alpha": 1,
    "factor": 4,
    "apply_preset": {
        "target_module": [
            "Attention",
            "FeedForward"
        ],
        "module_algo_map": {
            "FeedForward": {
                "factor": 4
            },
            "Attention": {
                "factor": 2
            }
        }
    }
}
```

## Datasets

### text-1mp
- Repeats: 100
- Total number of images: ~13221
- Total number of aspect buckets: 2
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### signs
- Repeats: 150
- Total number of images: ~420
- Total number of aspect buckets: 14
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### moviecollection
- Repeats: 0
- Total number of images: ~1983
- Total number of aspect buckets: 13
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### bookcovers
- Repeats: 0
- Total number of images: ~927
- Total number of aspect buckets: 24
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### shutterstock
- Repeats: 0
- Total number of images: ~21111
- Total number of aspect buckets: 30
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### cinemamix-1mp
- Repeats: 0
- Total number of images: ~7425
- Total number of aspect buckets: 3
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### anatomy
- Repeats: 5
- Total number of images: ~16440
- Total number of aspect buckets: 4
- Resolution: 1.048576 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### signs-512
- Repeats: 0
- Total number of images: ~417
- Total number of aspect buckets: 11
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### moviecollection-512
- Repeats: 0
- Total number of images: ~1971
- Total number of aspect buckets: 6
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### bookcovers-512
- Repeats: 0
- Total number of images: ~918
- Total number of aspect buckets: 9
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### shutterstock-512
- Repeats: 0
- Total number of images: ~21096
- Total number of aspect buckets: 18
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### cinemamix-1mp-512
- Repeats: 0
- Total number of images: ~7422
- Total number of aspect buckets: 3
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### anatomy-512
- Repeats: 5
- Total number of images: ~16437
- Total number of aspect buckets: 4
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### signs-1440
- Repeats: 100
- Total number of images: ~423
- Total number of aspect buckets: 25
- Resolution: 2.0736 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### moviecollection-1440
- Repeats: 0
- Total number of images: ~2007
- Total number of aspect buckets: 35
- Resolution: 2.0736 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### bookcovers-1440
- Repeats: 0
- Total number of images: ~933
- Total number of aspect buckets: 22
- Resolution: 2.0736 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### shutterstock-1440
- Repeats: 0
- Total number of images: ~21111
- Total number of aspect buckets: 37
- Resolution: 2.0736 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### cinemamix-1mp-1440
- Repeats: 0
- Total number of images: ~7425
- Total number of aspect buckets: 3
- Resolution: 2.0736 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No
### anatomy-1440
- Repeats: 5
- Total number of images: ~16458
- Total number of aspect buckets: 4
- Resolution: 2.0736 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No


## Inference


```python
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights


def download_adapter(repo_id: str):
    import os
    from huggingface_hub import hf_hub_download
    adapter_filename = "pytorch_lora_weights.safetensors"
    cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
    cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
    path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
    path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
    os.makedirs(path_to_adapter, exist_ok=True)
    hf_hub_download(
        repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
    )

    return path_to_adapter_file
    
model_id = 'stabilityai/stable-diffusion-3.5-medium'
adapter_repo_id = 'bghira/sd35m-photo-clip_value-shift3'
adapter_filename = 'pytorch_lora_weights.safetensors'
adapter_file_path = download_adapter(repo_id=adapter_repo_id)
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
wrapper.merge_to()

prompt = "A photo-realistic image of a cat"
negative_prompt = 'ugly, cropped, blurry, low-quality, mediocre average'

## Optional: quantise the model to save on vram.
## Note: The model was quantised during training, and so it is recommended to do the same during inference time.
from optimum.quanto import quantize, freeze, qint8
quantize(pipeline.transformer, weights=qint8)
freeze(pipeline.transformer)
    
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
image = pipeline(
    prompt=prompt,
    negative_prompt=negative_prompt,
    num_inference_steps=30,
    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
    width=1024,
    height=1024,
    guidance_scale=6.0,
).images[0]
image.save("output.png", format="PNG")
```



## Exponential Moving Average (EMA)

SimpleTuner generates a safetensors variant of the EMA weights and a pt file.

The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning.

The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights.