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stable-diffusion-v1-5-openvino-8bit

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OpenVINO
stable-diffusion
stable-diffusion-diffusers
nncf
8-bit precision
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  1. vae_encoder/openvino_model.xml +87 -83
vae_encoder/openvino_model.xml CHANGED
@@ -1,5 +1,5 @@
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6948
  <port id="0" precision="I64">
@@ -6972,7 +6972,7 @@
6972
  </port>
6973
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6974
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6975
- <layer id="403" name="Constant_1438730" type="Const" version="opset1">
6976
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6977
  <output>
6978
  <port id="0" precision="I64">
@@ -7010,7 +7010,7 @@
7010
  </port>
7011
  </output>
7012
  </layer>
7013
- <layer id="406" name="Convert_1573922" type="Convert" version="opset1">
7014
  <data destination_type="f16" />
7015
  <input>
7016
  <port id="0" precision="U8">
@@ -7034,7 +7034,7 @@
7034
  </port>
7035
  </output>
7036
  </layer>
7037
- <layer id="408" name="Convert_1573925" type="Convert" version="opset1">
7038
  <data destination_type="f16" />
7039
  <input>
7040
  <port id="0" precision="U8">
@@ -7132,7 +7132,7 @@
7132
  </port>
7133
  </output>
7134
  </layer>
7135
- <layer id="414" name="Constant_1438614" type="Const" version="opset1">
7136
  <data element_type="f32" shape="1, 1, 512" offset="29505820" size="2048" />
7137
  <output>
7138
  <port id="0" precision="FP32">
@@ -7323,7 +7323,7 @@
7323
  </port>
7324
  </output>
7325
  </layer>
7326
- <layer id="426" name="Convert_1573801" type="Convert" version="opset1">
7327
  <data destination_type="f16" />
7328
  <input>
7329
  <port id="0" precision="U8">
@@ -7353,7 +7353,7 @@
7353
  </port>
7354
  </output>
7355
  </layer>
7356
- <layer id="428" name="Convert_1573804" type="Convert" version="opset1">
7357
  <data destination_type="f16" />
7358
  <input>
7359
  <port id="0" precision="U8">
@@ -7583,7 +7583,7 @@
7583
  </port>
7584
  </output>
7585
  </layer>
7586
- <layer id="441" name="Convert_1573812" type="Convert" version="opset1">
7587
  <data destination_type="f16" />
7588
  <input>
7589
  <port id="0" precision="U8">
@@ -7613,7 +7613,7 @@
7613
  </port>
7614
  </output>
7615
  </layer>
7616
- <layer id="443" name="Convert_1573815" type="Convert" version="opset1">
7617
  <data destination_type="f16" />
7618
  <input>
7619
  <port id="0" precision="U8">
@@ -7868,7 +7868,7 @@
7868
  </port>
7869
  </output>
7870
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7871
- <layer id="457" name="Convert_1573999" type="Convert" version="opset1">
7872
  <data destination_type="f16" />
7873
  <input>
7874
  <port id="0" precision="U8">
@@ -7898,7 +7898,7 @@
7898
  </port>
7899
  </output>
7900
  </layer>
7901
- <layer id="459" name="Convert_1574002" type="Convert" version="opset1">
7902
  <data destination_type="f16" />
7903
  <input>
7904
  <port id="0" precision="U8">
@@ -8069,7 +8069,7 @@
8069
  </port>
8070
  </output>
8071
  </layer>
8072
- <layer id="468" name="Convert_1574032" type="Convert" version="opset1">
8073
  <data destination_type="f16" />
8074
  <input>
8075
  <port id="0" precision="U8">
@@ -8099,7 +8099,7 @@
8099
  </port>
8100
  </output>
8101
  </layer>
8102
- <layer id="470" name="Convert_1574035" type="Convert" version="opset1">
8103
  <data destination_type="f16" />
8104
  <input>
8105
  <port id="0" precision="U8">
@@ -8259,7 +8259,7 @@
8259
  </port>
8260
  </output>
8261
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8262
- <layer id="478" name="Result_1434803" type="Result" version="opset1">
8263
  <input>
8264
  <port id="0" precision="FP32">
8265
  <dim>-1</dim>
@@ -8765,7 +8765,7 @@
8765
  <edge from-layer="477" from-port="2" to-layer="478" to-port="0" />
8766
  </edges>
8767
  <rt_info>
8768
- <Runtime_version value="2024.5.0-17227-2441dcdbcf2" />
8769
  <conversion_parameters>
8770
  <framework value="pytorch" />
8771
  <is_python_object value="True" />
@@ -8773,9 +8773,10 @@
8773
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8774
  <friendly_names_were_updated value="True" />
8775
  <weight_compression>
8776
- <advanced_parameters value="{'awq_params': {'subset_size': 32, 'percent_to_apply': 0.002, 'alpha_min': 0.0, 'alpha_max': 1.0, 'steps': 100}, 'scale_estimation_params': {'subset_size': 64, 'initial_steps': 5, 'scale_steps': 5, 'weight_penalty': -1.0}, 'gptq_params': {'damp_percent': 0.1, 'block_size': 128, 'subset_size': 128}, 'lora_correction_params': {'adapter_rank': 8, 'num_iterations': 3, 'apply_regularization': True, 'subset_size': 128, 'use_int8_adapters': True}}" />
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  <all_layers value="False" />
8778
  <awq value="False" />
 
8779
  <gptq value="False" />
8780
  <group_size value="-1" />
8781
  <ignored_scope value="[]" />
@@ -8787,11 +8788,14 @@
8787
  </weight_compression>
8788
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8789
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8790
- <diffusers_version value="1.23.3" />
8791
- <optimum_intel_version value="1.21.0.dev0+5f539d5" />
8792
  <optimum_version value="1.23.3" />
8793
  <pytorch_version value="2.4.1+cpu" />
8794
  <transformers_version value="4.45.2" />
8795
  </optimum>
 
 
 
8796
  </rt_info>
8797
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2
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4
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  <data shape="?,3,?,?" element_type="f32" />
 
23
  </port>
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289
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313
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316
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317
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319
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543
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549
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573
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828
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830
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832
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1124
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1314
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1350
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3042
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3272
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3302
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3532
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3562
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3817
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3848
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4077
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4107
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4303
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4560
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4563
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4564
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4593
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4594
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4823
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4853
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4854
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5104
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5105
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5107
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5108
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5109
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5133
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5134
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5135
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5138
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5139
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5365
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5368
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5369
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5394
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5395
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5398
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5399
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5648
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5649
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5650
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5652
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5653
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5654
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5678
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5679
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5680
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5681
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5682
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5683
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5684
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5909
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5910
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5911
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5912
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5913
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5914
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5939
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5940
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5941
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5942
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5943
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5944
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6123
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6124
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6125
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6127
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6129
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6255
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6256
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6257
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6258
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6259
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6260
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6278
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6279
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6280
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6281
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6282
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6283
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6284
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6376
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6377
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6378
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6380
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6382
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6408
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6409
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6410
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6411
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6412
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6413
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6414
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6437
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6438
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6439
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6440
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6441
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6442
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6477
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6478
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6881
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8071
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8768
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8770
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8773
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8774
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8775
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8776
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8780
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8788
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8789
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+ <optimum_intel_version value="1.21.0.dev0+41637d0" />
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8795
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8796
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8797
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8798
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8799
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8800
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8801
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