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Ming-UniVision-16B-A3B

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  1. .gitattributes +1 -0
  2. README.md +658 -0
  3. assets/0830-mingtok-fig1.jpg +3 -0
  4. assets/ming-univision.jpg +0 -0
  5. config.json +393 -0
  6. generation_config.json +4 -0
  7. model-00001-of-00008.safetensors +3 -0
  8. model-00002-of-00008.safetensors +3 -0
  9. model-00003-of-00008.safetensors +3 -0
  10. model-00004-of-00008.safetensors +3 -0
  11. model-00005-of-00008.safetensors +3 -0
  12. model-00006-of-00008.safetensors +3 -0
  13. model-00007-of-00008.safetensors +3 -0
  14. model-00008-of-00008.safetensors +3 -0
  15. model.safetensors.index.json +0 -0
  16. preprocessor_config.json +58 -0
  17. special_tokens_map.json +45 -0
  18. tokenizer.json +0 -0
  19. tokenizer_config.json +2333 -0
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1
+ ## Ming-UniVision: Joint Image Understanding and Generation with a Unified Continuous Tokenizer
2
+
3
+ <p align="center">📑 <a href="">Technical Report</a>｜📖<a href="https://huggingface.co/inclusionAI/Ming-UniVision-16B-A3B">Project Page</a> ｜🤗 <a href="https://huggingface.co/inclusionAI/Ming-UniVision-16B-A3B">Hugging Face</a>｜ 🤖 <a href="https://www.modelscope.cn/models/inclusionAI/Ming-UniVision-16B-A3B">ModelScope</a>
4
+
5
+ ## Key Features
6
+ - 🌐 **First Unified Autoregressive MLLM with Continuous Vision Tokens:** Ming-UniVision is the first multimodal large language model that natively integrates continuous visual representations from MingTok into a next-token prediction (NTP) framework—unifying vision and language under a single autoregressive paradigm without discrete quantization or modality-specific heads.
7
+ - ⚡ **3.5× Faster Convergence in Joint Vision-Language Training:** The coherent representational space between understanding and generation—enabled by MingTok—reduces optimization conflicts across tasks, leading to dramatically faster convergence during end-to-end multimodal pretraining.
8
+ - 🔄 **Multi-Round In-Context Vision Tasks:** Ming-UniVision supports iterative understanding, generation, and editing entirely within the continuous latent space—without the need to decode intermediate states into images, enabling efficient and coherent multimodal reasoning.Users can alternate between asking questions and requesting edits, just like conversing with a human.
9
+
10
+ <div align="center">
11
+ <img src="assets/0830-mingtok-fig1.jpg" alt="Conceptual comparison and qualitative examples" width="80%"/>
12
+ </div>
13
+
14
+ **Figure 1: Conceptual comparison and qualitative examples of Ming-UniVision built upon MingTok.**
15
+
16
+ <div align="center">
17
+ <img src="assets/ming-univision.jpg" alt="Model Architecture" width="80%"/>
18
+ </div>
19
+
20
+ **Figure 2: Multi-Round image understanding, generation and editing architecture of Ming-UniVision, powered by MingTok.**
21
+
22
+ ## Usage
23
+ ```python
24
+
25
+ from mingunivisioninfer import MingUniVisionInfer, tensor_to_pil
26
+
27
+ model = MingUniVisionInfer("/input/wuyou.zc/pretrained/MingTok20250930")
28
+
29
+ # image generation
30
+ image_gen_prompt = "A beautiful girl."
31
+ messages = [
32
+ {"role": "HUMAN",
33
+ "content": [{"type": "text", "text": image_gen_prompt},],
34
+ }]
35
+
36
+ img_tensor = model.generate(messages, max_new_tokens=512, image_gen=True, image_gen_prompt=image_gen_prompt, image_gen_height=512, image_gen_width=512)
37
+ pil_img = tensor_to_pil(img_tensor)
38
+ pil_img.save("a_beautiful_girl.jpg")
39
+
40
+ # image understanding
41
+ messages = [{
42
+ "role": "HUMAN",
43
+ "content": [
44
+ {"type": "image", "image": "example.jpg"},
45
+ {"type": "text", "text": "Please describe the picture."},
46
+ ],
47
+ }]
48
+
49
+ output_text = model.generate(messages, max_new_tokens=512)
50
+ print(output_text)
51
+
52
+ # text generation
53
+ messages = [{
54
+ "role": "HUMAN",
55
+ "content": [
56
+ {"type": "text", "text": "请详细介绍鹦鹉的习性。"},
57
+ ],
58
+ }]
59
+
60
+ output_text = model.generate(messages, max_new_tokens=512)
61
+ print(output_text)
62
+ ```
63
+ ## Performance
64
+ ### Image Reconstruction
65
+
66
+ <!DOCTYPE html>
67
+ <html lang="en">
68
+ <head>
69
+ <meta charset="UTF-8" />
70
+ <title>Quantitative Evaluations on Multimodal Benchmarks</title>
71
+ <style>
72
+ body {
73
+ font-family: Arial, sans-serif;
74
+ margin: 20px;
75
+ }
76
+ table {
77
+ width: 100%;
78
+ border-collapse: collapse;
79
+ font-size: 12px;
80
+ }
81
+ th, td {
82
+ border: 1px solid #ccc;
83
+ padding: 6px 8px;
84
+ text-align: center;
85
+ }
86
+ thead th {
87
+ background-color: #f0f0f0;
88
+ font-weight: bold;
89
+ }
90
+ .section-row {
91
+ background-color: #f9f9f9;
92
+ text-align: center;
93
+ font-style: italic;
94
+ }
95
+ .dash-line {
96
+ border-top: 1px dashed #aaa;
97
+ }
98
+ .uparrow {
99
+ font-size: 10px; vertical-align: super;
100
+ }
101
+ </style>
102
+ </head>
103
+ <body>
104
+
105
+ <table>
106
+ <caption>
107
+ <strong>Table 1. Quantitative evaluations</strong> on MMBench, MMStar, MMMU, MathVista, HallusionBench, AI2D, MM-Vet, OCRBench, and MME.
108
+ </caption>
109
+ <thead>
110
+ <tr>
111
+ <th>Model</th>
112
+ <th>MMB&nbsp;<span class="uparrow">↑</span></th>
113
+ <th>MMS&nbsp;<span class="uparrow">↑</span></th>
114
+ <th>MMMU&nbsp;<span class="uparrow">↑</span></th>
115
+ <th>MathV&nbsp;<span class="uparrow">↑</span></th>
116
+ <th>Hall&nbsp;<span class="uparrow">↑</span></th>
117
+ <th>AI2D&nbsp;<span class="uparrow">↑</span></th>
118
+ <th>MM-Vet&nbsp;<span class="uparrow">↑</span></th>
119
+ <th>OCRBench&nbsp;<span class="uparrow">↑</span></th>
120
+ <th>MME&nbsp;<span class="uparrow">↑</span></th>
121
+ </tr>
122
+ </thead>
123
+ <tbody>
124
+ <!-- Understanding Only -->
125
+ <tr class="section-row">
126
+ <td colspan="10"><em>Understanding Only</em></td>
127
+ </tr>
128
+ <tr>
129
+ <td>Emu3-Chat</td>
130
+ <td>58.5</td>
131
+ <td>-</td>
132
+ <td>31.6</td>
133
+ <td>-</td>
134
+ <td>-</td>
135
+ <td>-</td>
136
+ <td>37.2</td>
137
+ <td>687</td>
138
+ <td>-</td>
139
+ </tr>
140
+ <tr>
141
+ <td>Qwen2.5-VL-3B</td>
142
+ <td>79.1</td>
143
+ <td>55.9</td>
144
+ <td>53.1</td>
145
+ <td>62.3</td>
146
+ <td>46.3</td>
147
+ <td>81.6</td>
148
+ <td>-</td>
149
+ <td>797</td>
150
+ <td>2157</td>
151
+ </tr>
152
+ <tr>
153
+ <td>Qwen2.5-VL-7B</td>
154
+ <td>83.5</td>
155
+ <td>63.9</td>
156
+ <td>58.6</td>
157
+ <td>68.2</td>
158
+ <td>52.9</td>
159
+ <td>83.9</td>
160
+ <td>67.1</td>
161
+ <td>864</td>
162
+ <td>2347</td>
163
+ </tr>
164
+ <tr>
165
+ <td>InternVL2.5-4B</td>
166
+ <td>81.1</td>
167
+ <td>58.3</td>
168
+ <td>52.3</td>
169
+ <td>60.5</td>
170
+ <td>46.3</td>
171
+ <td>81.4</td>
172
+ <td>60.6</td>
173
+ <td>828</td>
174
+ <td>2338</td>
175
+ </tr>
176
+ <tr>
177
+ <td>InternVL2.5-8B</td>
178
+ <td>84.6</td>
179
+ <td>62.8</td>
180
+ <td>56.0</td>
181
+ <td>64.4</td>
182
+ <td>50.1</td>
183
+ <td>84.5</td>
184
+ <td>62.8</td>
185
+ <td>822</td>
186
+ <td>2344</td>
187
+ </tr>
188
+ <tr>
189
+ <td>DeepSeek-VL2</td>
190
+ <td>79.6</td>
191
+ <td>61.3</td>
192
+ <td>51.1</td>
193
+ <td>62.8</td>
194
+ <td>-</td>
195
+ <td>81.4</td>
196
+ <td>-</td>
197
+ <td>811</td>
198
+ <td>2253</td>
199
+ </tr>
200
+ <!-- Unified model, Separate representation -->
201
+ <tr class="section-row">
202
+ <td colspan="10"><em>Unified model, Separate representation</em></td>
203
+ </tr>
204
+ <tr>
205
+ <td>Janus-Pro-7B</td>
206
+ <td>79.2</td>
207
+ <td>-</td>
208
+ <td>41.0</td>
209
+ <td>-</td>
210
+ <td>-</td>
211
+ <td>-</td>
212
+ <td>50.0</td>
213
+ <td>-</td>
214
+ <td>-</td>
215
+ </tr>
216
+ <tr>
217
+ <td>LMFusion</td>
218
+ <td>-</td>
219
+ <td>-</td>
220
+ <td>41.7</td>
221
+ <td>-</td>
222
+ <td>-</td>
223
+ <td>-</td>
224
+ <td>-</td>
225
+ <td>-</td>
226
+ <td>1603</td>
227
+ </tr>
228
+ <tr>
229
+ <td>MetaQuery-L</td>
230
+ <td>78.6</td>
231
+ <td>-</td>
232
+ <td>53.1</td>
233
+ <td>-</td>
234
+ <td>-</td>
235
+ <td>-</td>
236
+ <td>63.2</td>
237
+ <td>-</td>
238
+ <td>-</td>
239
+ </tr>
240
+ <tr>
241
+ <td>Show-o2-7B</td>
242
+ <td>79.3</td>
243
+ <td>56.6</td>
244
+ <td>48.9</td>
245
+ <td>-</td>
246
+ <td>-</td>
247
+ <td>78.6</td>
248
+ <td>-</td>
249
+ <td>-</td>
250
+ <td>-</td>
251
+ </tr>
252
+ <tr>
253
+ <td>BLIP3-o 4B</td>
254
+ <td>78.6</td>
255
+ <td>-</td>
256
+ <td>46.6</td>
257
+ <td>-</td>
258
+ <td>-</td>
259
+ <td>-</td>
260
+ <td>60.1</td>
261
+ <td>-</td>
262
+ <td>2161</td>
263
+ </tr>
264
+ <tr>
265
+ <td>BAGEL</td>
266
+ <td>85.0</td>
267
+ <td>-</td>
268
+ <td>55.3</td>
269
+ <td>73.1</td>
270
+ <td>-</td>
271
+ <td>-</td>
272
+ <td>67.2</td>
273
+ <td>-</td>
274
+ <td>2388</td>
275
+ </tr>
276
+ <!-- Unified model, Unified representation -->
277
+ <tr class="section-row">
278
+ <td colspan="10"><em>Unified model, Unified representation</em></td>
279
+ </tr>
280
+ <tr>
281
+ <td>VILA-U</td>
282
+ <td>-</td>
283
+ <td>-</td>
284
+ <td>-</td>
285
+ <td>-</td>
286
+ <td>-</td>
287
+ <td>-</td>
288
+ <td>33.5</td>
289
+ <td>-</td>
290
+ <td>1402</td>
291
+ </tr>
292
+ <tr>
293
+ <td>TokenFlow-XL</td>
294
+ <td>76.8</td>
295
+ <td>-</td>
296
+ <td>43.2</td>
297
+ <td>-</td>
298
+ <td>-</td>
299
+ <td>-</td>
300
+ <td>48.2</td>
301
+ <td>-</td>
302
+ <td>1922</td>
303
+ </tr>
304
+ <tr>
305
+ <td>UniTok</td>
306
+ <td>-</td>
307
+ <td>-</td>
308
+ <td>-</td>
309
+ <td>-</td>
310
+ <td>-</td>
311
+ <td>-</td>
312
+ <td>33.9</td>
313
+ <td>-</td>
314
+ <td>1448</td>
315
+ </tr>
316
+ <tr>
317
+ <td>Harmon-1.5B</td>
318
+ <td>65.5</td>
319
+ <td>-</td>
320
+ <td>38.9</td>
321
+ <td>-</td>
322
+ <td>-</td>
323
+ <td>-</td>
324
+ <td>-</td>
325
+ <td>-</td>
326
+ <td>1476</td>
327
+ </tr>
328
+ <tr>
329
+ <td>TokLIP</td>
330
+ <td>67.6</td>
331
+ <td>-</td>
332
+ <td>43.1</td>
333
+ <td>-</td>
334
+ <td>-</td>
335
+ <td>-</td>
336
+ <td>29.8</td>
337
+ <td>-</td>
338
+ <td>-</td>
339
+ </tr>
340
+ <!-- Dashed line separator -->
341
+ <tr><td colspan="10" style="border-top: 1px dashed #aaa;"></td></tr>
342
+ <!-- Ours -->
343
+ <tr>
344
+ <td><strong>Ming-UniVision-16B-A3B (Ours)</strong></td>
345
+ <td>78.5</td>
346
+ <td>63.7</td>
347
+ <td>40.3</td>
348
+ <td>66.6</td>
349
+ <td>47.8</td>
350
+ <td>82.8</td>
351
+ <td>64.2</td>
352
+ <td>724</td>
353
+ <td>2023</td>
354
+ </tr>
355
+ </tbody>
356
+ </table>
357
+
358
+ </body>
359
+ </html>
360
+
361
+ <!DOCTYPE html>
362
+ <html lang="en">
363
+ <head>
364
+ <meta charset="UTF-8" />
365
+ <title>Text-to-Image Generation Evaluation</title>
366
+ <style>
367
+ body {
368
+ font-family: Arial, sans-serif;
369
+ margin: 20px;
370
+ }
371
+ table {
372
+ width: 100%;
373
+ border-collapse: collapse;
374
+ font-size: 12px;
375
+ }
376
+ th, td {
377
+ border: 1px solid #ccc;
378
+ padding: 6px 8px;
379
+ text-align: center;
380
+ }
381
+ thead th {
382
+ background-color: #f0f0f0;
383
+ font-weight: bold;
384
+ }
385
+ .section-row {
386
+ background-color: #f9f9f9;
387
+ text-align: center;
388
+ font-style: italic;
389
+ }
390
+ .uparrow {
391
+ font-size: 10px; vertical-align: super;
392
+ }
393
+ .dagger {
394
+ font-size: 10px; color: gray;
395
+ }
396
+ caption {
397
+ font-weight: bold;
398
+ font-size: 14px;
399
+ margin: 10px 0;
400
+ text-align: left;
401
+ }
402
+ </style>
403
+ </head>
404
+ <body>
405
+
406
+ <table>
407
+ <caption>
408
+ <strong>Table 2. Evaluation of text-to-image generation ability</strong> on GenEval and DPG-Bench.
409
+ <span class="dagger">† denotes performance obtained by rewritten prompts.</span>
410
+ </caption>
411
+ <thead>
412
+ <tr>
413
+ <th>Method</th>
414
+ <th>Single Obj.&nbsp;<span class="uparrow">↑</span></th>
415
+ <th>Two Obj.&nbsp;<span class="uparrow">↑</span></th>
416
+ <th>Counting&nbsp;<span class="uparrow">↑</span></th>
417
+ <th>Colors&nbsp;<span class="uparrow">↑</span></th>
418
+ <th>Position&nbsp;<span class="uparrow">↑</span></th>
419
+ <th>Color Attri.&nbsp;<span class="uparrow">↑</span></th>
420
+ <th>Overall&nbsp;<span class="uparrow">↑</span></th>
421
+ <th>DPG-Bench&nbsp;<span class="uparrow">↑</span></th>
422
+ </tr>
423
+ </thead>
424
+ <tbody>
425
+ <!-- Generation Only -->
426
+ <tr class="section-row">
427
+ <td colspan="9"><em>Generation Only</em></td>
428
+ </tr>
429
+ <tr>
430
+ <td>LlamaGen</td>
431
+ <td>0.71</td>
432
+ <td>0.34</td>
433
+ <td>0.21</td>
434
+ <td>0.58</td>
435
+ <td>0.07</td>
436
+ <td>0.04</td>
437
+ <td>0.32</td>
438
+ <td>-</td>
439
+ </tr>
440
+ <tr>
441
+ <td>PixArt-α</td>
442
+ <td>0.98</td>
443
+ <td>0.50</td>
444
+ <td>0.44</td>
445
+ <td>0.80</td>
446
+ <td>0.08</td>
447
+ <td>0.07</td>
448
+ <td>0.48</td>
449
+ <td>-</td>
450
+ </tr>
451
+ <tr>
452
+ <td>SDv2.1</td>
453
+ <td>0.98</td>
454
+ <td>0.51</td>
455
+ <td>0.44</td>
456
+ <td>0.85</td>
457
+ <td>0.07</td>
458
+ <td>0.17</td>
459
+ <td>0.50</td>
460
+ <td>-</td>
461
+ </tr>
462
+ <tr>
463
+ <td>DALL-E 2</td>
464
+ <td>0.94</td>
465
+ <td>0.66</td>
466
+ <td>0.49</td>
467
+ <td>0.77</td>
468
+ <td>0.10</td>
469
+ <td>0.19</td>
470
+ <td>0.52</td>
471
+ <td>-</td>
472
+ </tr>
473
+ <tr>
474
+ <td>Emu3-Gen</td>
475
+ <td>0.98</td>
476
+ <td>0.71</td>
477
+ <td>0.34</td>
478
+ <td>0.81</td>
479
+ <td>0.17</td>
480
+ <td>0.21</td>
481
+ <td>0.54</td>
482
+ <td>80.60</td>
483
+ </tr>
484
+ <tr>
485
+ <td>SDXL</td>
486
+ <td>0.98</td>
487
+ <td>0.74</td>
488
+ <td>0.39</td>
489
+ <td>0.85</td>
490
+ <td>0.15</td>
491
+ <td>0.23</td>
492
+ <td>0.55</td>
493
+ <td>74.65</td>
494
+ </tr>
495
+ <tr>
496
+ <td>DALL-E 3</td>
497
+ <td>0.96</td>
498
+ <td>0.87</td>
499
+ <td>0.47</td>
500
+ <td>0.83</td>
501
+ <td>0.43</td>
502
+ <td>0.45</td>
503
+ <td>0.67</td>
504
+ <td>83.50</td>
505
+ </tr>
506
+ <tr>
507
+ <td>SD3-Medium</td>
508
+ <td>0.99</td>
509
+ <td><strong>0.94</strong></td>
510
+ <td>0.72</td>
511
+ <td>0.89</td>
512
+ <td>0.33</td>
513
+ <td>0.60</td>
514
+ <td>0.74</td>
515
+ <td>84.08</td>
516
+ </tr>
517
+ <!-- Unified model, Separate representation -->
518
+ <tr class="section-row">
519
+ <td colspan="9"><em>Unified model, Separate representation</em></td>
520
+ </tr>
521
+ <tr>
522
+ <td>Show-o</td>
523
+ <td>0.95</td>
524
+ <td>0.52</td>
525
+ <td>0.49</td>
526
+ <td>0.82</td>
527
+ <td>0.11</td>
528
+ <td>0.28</td>
529
+ <td>0.53</td>
530
+ <td>-</td>
531
+ </tr>
532
+ <tr>
533
+ <td>Ming-Lite-Uni</td>
534
+ <td>0.99</td>
535
+ <td>0.76</td>
536
+ <td>0.53</td>
537
+ <td>0.87</td>
538
+ <td>0.26</td>
539
+ <td>0.30</td>
540
+ <td>0.62</td>
541
+ <td>-</td>
542
+ </tr>
543
+ <tr>
544
+ <td>Janus-Pro-1B</td>
545
+ <td>0.98</td>
546
+ <td>0.82</td>
547
+ <td>0.51</td>
548
+ <td>0.89</td>
549
+ <td>0.65</td>
550
+ <td>0.56</td>
551
+ <td>0.73</td>
552
+ <td>82.63</td>
553
+ </tr>
554
+ <tr>
555
+ <td>Janus-Pro-7B</td>
556
+ <td>0.99</td>
557
+ <td>0.89</td>
558
+ <td>0.59</td>
559
+ <td>0.90</td>
560
+ <td>0.79</td>
561
+ <td>0.66</td>
562
+ <td>0.80</td>
563
+ <td>84.19</td>
564
+ </tr>
565
+ <tr>
566
+ <td>Show-o2-7B</td>
567
+ <td><strong>1.00</strong></td>
568
+ <td>0.87</td>
569
+ <td>0.58</td>
570
+ <td>0.92</td>
571
+ <td>0.52</td>
572
+ <td>0.62</td>
573
+ <td>0.76</td>
574
+ <td><strong>86.14</strong></td>
575
+ </tr>
576
+ <tr>
577
+ <td>MetaQuery-L†</td>
578
+ <td>-</td>
579
+ <td>-</td>
580
+ <td>-</td>
581
+ <td>-</td>
582
+ <td>-</td>
583
+ <td>-</td>
584
+ <td>0.78</td>
585
+ <td>81.10</td>
586
+ </tr>
587
+ <tr>
588
+ <td>Blip3-o 4B</td>
589
+ <td>-</td>
590
+ <td>-</td>
591
+ <td>-</td>
592
+ <td>-</td>
593
+ <td>-</td>
594
+ <td>-</td>
595
+ <td>0.81</td>
596
+ <td>79.36</td>
597
+ </tr>
598
+ <tr>
599
+ <td>BAGEL</td>
600
+ <td>0.99</td>
601
+ <td><strong>0.94</strong></td>
602
+ <td><strong>0.81</strong></td>
603
+ <td>0.88</td>
604
+ <td>0.64</td>
605
+ <td>0.63</td>
606
+ <td>0.82</td>
607
+ <td>-</td>
608
+ </tr>
609
+ <!-- Unified model, Unified representation -->
610
+ <tr class="section-row">
611
+ <td colspan="9"><em>Unified model, Unified representation</em></td>
612
+ </tr>
613
+ <tr>
614
+ <td>Harmon-1.5B</td>
615
+ <td>0.99</td>
616
+ <td>0.86</td>
617
+ <td>0.66</td>
618
+ <td>0.85</td>
619
+ <td>0.74</td>
620
+ <td>0.48</td>
621
+ <td>0.79</td>
622
+ <td>-</td>
623
+ </tr>
624
+ <tr>
625
+ <td>TokenFlow-XL</td>
626
+ <td>0.95</td>
627
+ <td>0.60</td>
628
+ <td>0.41</td>
629
+ <td>0.81</td>
630
+ <td>0.16</td>
631
+ <td>0.24</td>
632
+ <td>0.55</td>
633
+ <td>73.38</td>
634
+ </tr>
635
+ <!-- Dashed line separator -->
636
+ <tr><td colspan="9" style="border-top: 1px dashed #aaa;"></td></tr>
637
+ <!-- Ours -->
638
+ <tr>
639
+ <td><strong>Ming-UniVision-16B-A3B (Ours)</strong></td>
640
+ <td><strong>1.00</strong></td>
641
+ <td>0.93</td>
642
+ <td>0.59</td>
643
+ <td><strong>0.93</strong></td>
644
+ <td><strong>0.92</strong></td>
645
+ <td><strong>0.70</strong></td>
646
+ <td><strong>0.85</strong></td>
647
+ <td>82.12</td>
648
+ </tr>
649
+ </tbody>
650
+ </table>
651
+
652
+ </body>
653
+ </html>
654
+
655
+
656
+
657
+ ## Reference
658
+ TBD.
assets/0830-mingtok-fig1.jpg ADDED

Git LFS Details

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  • Pointer size: 131 Bytes
  • Size of remote file: 355 kB
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