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  1. quanto-exps-2/benchmark.py +135 -0
  2. quanto-exps-2/benchmark_2.py +147 -0
  3. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@0-fuse@0.png +3 -0
  4. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@0-fuse@0_info.json +1 -0
  5. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@1-fuse@0.png +3 -0
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  10. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@int8-qte@1-fuse@0_info.json +1 -0
  11. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@none-qte@0-fuse@0.png +3 -0
  12. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@none-qte@0-fuse@0_info.json +1 -0
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  14. quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@none-qte@1-fuse@0_info.json +1 -0
  15. quanto-exps-2/ckpt@auraflow-bs@1-dtype@fp16-qtype@fp8-qte@0-fuse@0.png +3 -0
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  24. quanto-exps-2/ckpt@auraflow-bs@1-dtype@fp16-qtype@none-qte@0-fuse@0_info.json +1 -0
  25. quanto-exps-2/ckpt@auraflow-bs@1-dtype@fp16-qtype@none-qte@1-fuse@0.png +3 -0
  26. quanto-exps-2/ckpt@auraflow-bs@1-dtype@fp16-qtype@none-qte@1-fuse@0_info.json +1 -0
  27. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@fp8-qte@0-fuse@0.png +3 -0
  28. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@fp8-qte@0-fuse@0_info.json +1 -0
  29. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@fp8-qte@1-fuse@0.png +3 -0
  30. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@fp8-qte@1-fuse@0_info.json +1 -0
  31. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@int8-qte@0-fuse@0.png +3 -0
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  36. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@none-qte@0-fuse@0_info.json +1 -0
  37. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@none-qte@1-fuse@0.png +3 -0
  38. quanto-exps-2/ckpt@auraflow-bs@4-dtype@bf16-qtype@none-qte@1-fuse@0_info.json +1 -0
  39. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@fp8-qte@0-fuse@0.png +3 -0
  40. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@fp8-qte@0-fuse@0_info.json +1 -0
  41. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@fp8-qte@1-fuse@0.png +3 -0
  42. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@fp8-qte@1-fuse@0_info.json +1 -0
  43. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@int8-qte@0-fuse@0.png +3 -0
  44. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@int8-qte@0-fuse@0_info.json +1 -0
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  50. quanto-exps-2/ckpt@auraflow-bs@4-dtype@fp16-qtype@none-qte@1-fuse@0_info.json +1 -0
quanto-exps-2/benchmark.py ADDED
@@ -0,0 +1,135 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import argparse
2
+ from optimum.quanto import freeze, qfloat8, qint4, qint8, quantize
3
+ import torch
4
+ import json
5
+ import torch.utils.benchmark as benchmark
6
+ from diffusers import DiffusionPipeline
7
+ import gc
8
+
9
+
10
+ WARM_UP_ITERS = 5
11
+ PROMPT = "ghibli style, a fantasy landscape with castles"
12
+
13
+ TORCH_DTYPES = {"fp32": torch.float32, "fp16": torch.float16, "bf16": torch.bfloat16}
14
+ # QTYPES = {"fp8": qfloat8, "int8": qint8, "int4": qint4, "none": None}
15
+ QTYPES = {"fp8": qfloat8, "int8": qint8, "none": None}
16
+
17
+ PREFIXES = {
18
+ "stabilityai/stable-diffusion-3-medium-diffusers": "sd3",
19
+ "PixArt-alpha/PixArt-Sigma-XL-2-1024-MS": "pixart",
20
+ "fal/AuraFlow": "auraflow",
21
+ }
22
+
23
+ def flush():
24
+ """Wipes off memory."""
25
+ gc.collect()
26
+ torch.cuda.empty_cache()
27
+ torch.cuda.reset_max_memory_allocated()
28
+ torch.cuda.reset_peak_memory_stats()
29
+
30
+ def load_pipeline(ckpt_id, torch_dtype, qtype=None, exclude_layers=None, qte=False, fuse=False):
31
+ pipe = DiffusionPipeline.from_pretrained(ckpt_id, torch_dtype=torch_dtype).to("cuda")
32
+ if fuse:
33
+ pipe.transformer.fuse_qkv_projections()
34
+
35
+ if qtype:
36
+ quantize(pipe.transformer, weights=qtype, exclude=exclude_layers)
37
+ freeze(pipe.transformer)
38
+
39
+ if qte:
40
+ quantize(pipe.text_encoder, weights=qtype)
41
+ freeze(pipe.text_encoder)
42
+ if hasattr(pipe, "text_encoder_2"):
43
+ quantize(pipe.text_encoder_2, weights=qtype)
44
+ freeze(pipe.text_encoder_2)
45
+ if hasattr(pipe, "text_encoder_3"):
46
+ quantize(pipe.text_encoder_3, weights=qtype)
47
+ freeze(pipe.text_encoder_3)
48
+
49
+ pipe.set_progress_bar_config(disable=True)
50
+ return pipe
51
+
52
+
53
+ def run_inference(pipe, batch_size=1):
54
+ _ = pipe(
55
+ prompt=PROMPT,
56
+ num_images_per_prompt=batch_size,
57
+ generator=torch.manual_seed(0),
58
+ )
59
+
60
+
61
+ def benchmark_fn(f, *args, **kwargs):
62
+ t0 = benchmark.Timer(stmt="f(*args, **kwargs)", globals={"args": args, "kwargs": kwargs, "f": f})
63
+ return f"{(t0.blocked_autorange().mean):.3f}"
64
+
65
+
66
+ def bytes_to_giga_bytes(bytes):
67
+ return f"{(bytes / 1024 / 1024 / 1024):.3f}"
68
+
69
+
70
+ if __name__ == "__main__":
71
+ parser = argparse.ArgumentParser()
72
+ parser.add_argument(
73
+ "--ckpt_id",
74
+ type=str,
75
+ default="stabilityai/stable-diffusion-3-medium-diffusers",
76
+ choices=list(PREFIXES.keys()),
77
+ )
78
+ parser.add_argument("--batch_size", type=int, default=1)
79
+ parser.add_argument("--torch_dtype", type=str, default="fp16", choices=list(TORCH_DTYPES.keys()))
80
+ parser.add_argument("--qtype", type=str, default="none", choices=list(QTYPES.keys()))
81
+ parser.add_argument("--qte", type=int, default=0, help="Quantize text encoder")
82
+ parser.add_argument("--fuse", type=int, default=0)
83
+ parser.add_argument("--exclude_layers", metavar="N", type=str, nargs="*", default=None)
84
+ args = parser.parse_args()
85
+
86
+ flush()
87
+
88
+ print(
89
+ f"Running with ckpt_id: {args.ckpt_id}, batch_size: {args.batch_size}, torch_dtype: {args.torch_dtype}, qtype: {args.qtype}, qte: {bool(args.qte)}, {args.exclude_layers=}, {args.fuse=}"
90
+ )
91
+ pipeline = load_pipeline(
92
+ ckpt_id=args.ckpt_id,
93
+ torch_dtype=TORCH_DTYPES[args.torch_dtype],
94
+ qtype=QTYPES[args.qtype],
95
+ exclude_layers=args.exclude_layers,
96
+ qte=args.qte,
97
+ fuse=bool(args.fuse),
98
+ )
99
+
100
+ for _ in range(WARM_UP_ITERS):
101
+ run_inference(pipeline, args.batch_size)
102
+
103
+ time = benchmark_fn(run_inference, pipeline, args.batch_size)
104
+ torch.cuda.empty_cache()
105
+ memory = bytes_to_giga_bytes(torch.cuda.memory_allocated()) # in GBs.
106
+ print(
107
+ f"ckpt: {args.ckpt_id} batch_size: {args.batch_size}, qte: {args.qte}, {args.exclude_layers=} "
108
+ f"torch_dtype: {args.torch_dtype}, qtype: {args.qtype} in {time} seconds and {memory} GBs."
109
+ )
110
+
111
+ ckpt_id = PREFIXES[args.ckpt_id]
112
+ img_name = f"ckpt@{ckpt_id}-bs@{args.batch_size}-dtype@{args.torch_dtype}-qtype@{args.qtype}-qte@{args.qte}-fuse@{args.fuse}"
113
+ if args.exclude_layers:
114
+ exclude_layers = "_".join(args.exclude_layers)
115
+ img_name += f"-exclude@{exclude_layers}"
116
+ image = pipeline(
117
+ prompt=PROMPT,
118
+ num_images_per_prompt=args.batch_size,
119
+ generator=torch.manual_seed(0),
120
+ ).images[0]
121
+ image.save(f"{img_name}.png")
122
+
123
+ info = dict(
124
+ batch_size=args.batch_size,
125
+ memory=memory,
126
+ time=time,
127
+ dtype=args.torch_dtype,
128
+ qtype=args.qtype,
129
+ qte=args.qte,
130
+ exclude_layers=args.exclude_layers,
131
+ # fuse=args.fuse,
132
+ )
133
+ info_file = f"{img_name}_info.json"
134
+ with open(info_file, "w") as f:
135
+ json.dump(info, f)
quanto-exps-2/benchmark_2.py ADDED
@@ -0,0 +1,147 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import argparse
2
+ from optimum.quanto import freeze, qfloat8, qint4, qint8, quantize
3
+ import torch
4
+ import json
5
+ import torch.utils.benchmark as benchmark
6
+ from diffusers import DiffusionPipeline
7
+ import gc
8
+
9
+
10
+ WARM_UP_ITERS = 5
11
+ PROMPT = "ghibli style, a fantasy landscape with castles"
12
+
13
+ TORCH_DTYPES = {"fp32": torch.float32, "fp16": torch.float16, "bf16": torch.bfloat16}
14
+ QTYPES = {"fp8": qfloat8, "int8": qint8, "int4": qint4, "none": None}
15
+
16
+ PREFIXES = {
17
+ "stabilityai/stable-diffusion-3-medium-diffusers": "sd3",
18
+ }
19
+
20
+
21
+ def flush():
22
+ """Wipes off memory."""
23
+ gc.collect()
24
+ torch.cuda.empty_cache()
25
+ torch.cuda.reset_max_memory_allocated()
26
+ torch.cuda.reset_peak_memory_stats()
27
+
28
+
29
+ def load_pipeline(
30
+ ckpt_id, torch_dtype, qtype=None, exclude_layers=None, qte=False, first=False, second=False, third=False
31
+ ):
32
+ pipe = DiffusionPipeline.from_pretrained(ckpt_id, torch_dtype=torch_dtype).to("cuda")
33
+
34
+ if qtype:
35
+ quantize(pipe.transformer, weights=qtype, exclude=exclude_layers)
36
+ freeze(pipe.transformer)
37
+
38
+ if qte:
39
+ if first:
40
+ quantize(pipe.text_encoder, weights=qtype)
41
+ freeze(pipe.text_encoder)
42
+ if second:
43
+ quantize(pipe.text_encoder_2, weights=qtype)
44
+ freeze(pipe.text_encoder)
45
+ if third:
46
+ quantize(pipe.text_encoder_3, weights=qtype)
47
+ freeze(pipe.text_encoder_3)
48
+
49
+ pipe.set_progress_bar_config(disable=True)
50
+ return pipe
51
+
52
+
53
+ def run_inference(pipe, batch_size=1):
54
+ _ = pipe(
55
+ prompt=PROMPT,
56
+ num_images_per_prompt=batch_size,
57
+ generator=torch.manual_seed(0),
58
+ )
59
+
60
+
61
+ def benchmark_fn(f, *args, **kwargs):
62
+ t0 = benchmark.Timer(stmt="f(*args, **kwargs)", globals={"args": args, "kwargs": kwargs, "f": f})
63
+ return f"{(t0.blocked_autorange().mean):.3f}"
64
+
65
+
66
+ def bytes_to_giga_bytes(bytes):
67
+ return f"{(bytes / 1024 / 1024 / 1024):.3f}"
68
+
69
+
70
+ if __name__ == "__main__":
71
+ parser = argparse.ArgumentParser()
72
+ parser.add_argument(
73
+ "--ckpt_id",
74
+ type=str,
75
+ default="stabilityai/stable-diffusion-3-medium-diffusers",
76
+ choices=list(PREFIXES.keys()),
77
+ )
78
+ parser.add_argument("--batch_size", type=int, default=1)
79
+ parser.add_argument("--torch_dtype", type=str, default="fp16", choices=list(TORCH_DTYPES.keys()))
80
+ parser.add_argument("--qtype", type=str, default="none", choices=list(QTYPES.keys()))
81
+ parser.add_argument("--qte", type=int, default=0, help="Quantize text encoder")
82
+ parser.add_argument("--first", type=int, default=0, help="Quantize first text encoder")
83
+ parser.add_argument("--second", type=int, default=0, help="Quantize second text encoder")
84
+ parser.add_argument("--third", type=int, default=0, help="Quantize third text encoder")
85
+ parser.add_argument("--exclude_layers", metavar="N", type=str, nargs="*", default=None)
86
+ args = parser.parse_args()
87
+
88
+ flush()
89
+
90
+ print(
91
+ f"Running with ckpt_id: {args.ckpt_id}, batch_size: {args.batch_size}, torch_dtype: {args.torch_dtype}, qtype: {args.qtype}, qte: {bool(args.qte)}"
92
+ )
93
+ pipeline = load_pipeline(
94
+ ckpt_id=args.ckpt_id,
95
+ torch_dtype=TORCH_DTYPES[args.torch_dtype],
96
+ qtype=QTYPES[args.qtype],
97
+ exclude_layers=args.exclude_layers,
98
+ qte=args.qte,
99
+ first=args.first,
100
+ second=args.second,
101
+ third=args.third,
102
+ )
103
+
104
+ for _ in range(WARM_UP_ITERS):
105
+ run_inference(pipeline, args.batch_size)
106
+
107
+ time = benchmark_fn(run_inference, pipeline, args.batch_size)
108
+ memory = bytes_to_giga_bytes(torch.cuda.max_memory_allocated()) # in GBs.
109
+ print(
110
+ f"ckpt: {args.ckpt_id} batch_size: {args.batch_size}, qte: {args.qte}, "
111
+ f"torch_dtype: {args.torch_dtype}, qtype: {args.qtype} in {time} seconds and {memory} GBs."
112
+ )
113
+
114
+ ckpt_id = PREFIXES[args.ckpt_id]
115
+ img_name = f"ckpt@{ckpt_id}-bs@{args.batch_size}-dtype@{args.torch_dtype}-qtype@{args.qtype}-qte@{args.qte}"
116
+ if args.exclude_layers:
117
+ exclude_layers = "_".join(args.exclude_layers)
118
+ img_name += f"-exclude@{exclude_layers}"
119
+ if args.first:
120
+ img_name += f"-first@{args.first}"
121
+ if args.second:
122
+ img_name += f"-second@{args.second}"
123
+ if args.third:
124
+ img_name += f"-third@{args.third}"
125
+
126
+ image = pipeline(
127
+ prompt=PROMPT,
128
+ num_images_per_prompt=args.batch_size,
129
+ generator=torch.manual_seed(0),
130
+ ).images[0]
131
+ image.save(f"{img_name}.png")
132
+
133
+ info = dict(
134
+ batch_size=args.batch_size,
135
+ memory=memory,
136
+ time=time,
137
+ dtype=args.torch_dtype,
138
+ qtype=args.qtype,
139
+ qte=args.qte,
140
+ exclude_layers=args.exclude_layers,
141
+ first=args.first,
142
+ second=args.second,
143
+ third=args.third,
144
+ )
145
+ info_file = f"{img_name}_info.json"
146
+ with open(info_file, "w") as f:
147
+ json.dump(info, f)
quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@0-fuse@0.png ADDED

Git LFS Details

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quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@0-fuse@0_info.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"batch_size": 1, "memory": "8.861", "time": "14.298", "dtype": "bf16", "qtype": "fp8", "qte": 0, "exclude_layers": null}
quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@1-fuse@0.png ADDED

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  • SHA256: 64cdd76c6353c96cb27e0d54c7f3ab4c8602756df3ece6fe7e77e708dacd2dda
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quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@fp8-qte@1-fuse@0_info.json ADDED
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1
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quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@int8-qte@0-fuse@0.png ADDED

Git LFS Details

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quanto-exps-2/ckpt@auraflow-bs@1-dtype@bf16-qtype@int8-qte@0-fuse@0_info.json ADDED
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Git LFS Details

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  • Size of remote file: 2.11 MB
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Git LFS Details

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  • Size of remote file: 2.14 MB
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Git LFS Details

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  • Size of remote file: 2.14 MB
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Git LFS Details

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  • Size of remote file: 1.77 MB
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Git LFS Details

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  • Size of remote file: 1.77 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 2.21 MB
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Git LFS Details

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  • Size of remote file: 2.02 MB
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Git LFS Details

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  • Size of remote file: 2.19 MB
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Git LFS Details

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  • Size of remote file: 2.11 MB
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Git LFS Details

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  • Size of remote file: 2.14 MB
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Git LFS Details

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  • Size of remote file: 2.14 MB
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Git LFS Details

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  • Size of remote file: 1.77 MB
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Git LFS Details

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  • Size of remote file: 1.77 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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Git LFS Details

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  • Size of remote file: 1.78 MB
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