Add high-quality stateful three-style inpainting U-Net
Browse files
hq-v3/Unet.mlmodelc/analytics/coremldata.bin
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:0776280c592bd31e478eecd0cac5918984d48e629d1ffa5a9d6432a698448c9e
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size 243
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hq-v3/Unet.mlmodelc/coremldata.bin
ADDED
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@@ -0,0 +1,3 @@
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+
version https://git-lfs.github.com/spec/v1
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oid sha256:4cb24ed826e3e090138e99e3eb334e706d6b8bf733771fe034355268456e6834
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size 14009
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hq-v3/Unet.mlmodelc/metadata.json
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@@ -0,0 +1,1405 @@
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|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"shortDescription" : "Stable Diffusion generates images conditioned on text or other images as input through the diffusion process. Please refer to https:\/\/arxiv.org\/abs\/2112.10752 for details.",
|
| 4 |
+
"metadataOutputVersion" : "3.0",
|
| 5 |
+
"outputSchema" : [
|
| 6 |
+
{
|
| 7 |
+
"hasShapeFlexibility" : "0",
|
| 8 |
+
"isOptional" : "0",
|
| 9 |
+
"dataType" : "Float32",
|
| 10 |
+
"formattedType" : "MultiArray (Float32 1 × 4 × 64 × 64)",
|
| 11 |
+
"shortDescription" : "Same shape and dtype as the `sample` input. The predicted noise to facilitate the reverse diffusion (denoising) process",
|
| 12 |
+
"shape" : "[1, 4, 64, 64]",
|
| 13 |
+
"name" : "noise_pred",
|
| 14 |
+
"type" : "MultiArray"
|
| 15 |
+
}
|
| 16 |
+
],
|
| 17 |
+
"version" : "clover-image-tiny-inpaint-hq",
|
| 18 |
+
"modelParameters" : [
|
| 19 |
+
|
| 20 |
+
],
|
| 21 |
+
"author" : "Please refer to the Model Card available at huggingface.co\/clover-image-tiny-inpaint-hq",
|
| 22 |
+
"specificationVersion" : 9,
|
| 23 |
+
"storagePrecision" : "Float16",
|
| 24 |
+
"license" : "OpenRAIL (https:\/\/huggingface.co\/spaces\/CompVis\/stable-diffusion-license)",
|
| 25 |
+
"mlProgramOperationTypeHistogram" : {
|
| 26 |
+
"Ios18.expandDims" : 3,
|
| 27 |
+
"Ios18.mul" : 49,
|
| 28 |
+
"Ios18.cos" : 1,
|
| 29 |
+
"Ios18.softmax" : 32,
|
| 30 |
+
"Ios18.matmul" : 208,
|
| 31 |
+
"Ios18.batchNorm" : 61,
|
| 32 |
+
"UpsampleNearestNeighbor" : 3,
|
| 33 |
+
"Ios16.reduceMean" : 122,
|
| 34 |
+
"Ios18.realDiv" : 61,
|
| 35 |
+
"Ios18.sin" : 1,
|
| 36 |
+
"Split" : 16,
|
| 37 |
+
"Ios18.readState" : 144,
|
| 38 |
+
"Ios18.add" : 241,
|
| 39 |
+
"Ios18.layerNorm" : 48,
|
| 40 |
+
"Ios18.reshape" : 282,
|
| 41 |
+
"Ios18.conv" : 282,
|
| 42 |
+
"Ios18.concat" : 14,
|
| 43 |
+
"Ios18.silu" : 47,
|
| 44 |
+
"Ios18.sub" : 61,
|
| 45 |
+
"Ios18.transpose" : 109,
|
| 46 |
+
"Ios18.sqrt" : 61,
|
| 47 |
+
"Ios18.gelu" : 16,
|
| 48 |
+
"Ios18.cast" : 1,
|
| 49 |
+
"Ios18.square" : 61,
|
| 50 |
+
"Ios18.sliceByIndex" : 290
|
| 51 |
+
},
|
| 52 |
+
"computePrecision" : "Mixed (Float16, Float32, Int32)",
|
| 53 |
+
"stateSchema" : [
|
| 54 |
+
{
|
| 55 |
+
"dataType" : "Float16",
|
| 56 |
+
"isOptional" : "0",
|
| 57 |
+
"formattedType" : "State (Float16 48 × 320 × 1 × 1)",
|
| 58 |
+
"shortDescription" : "",
|
| 59 |
+
"shape" : "[48, 320, 1, 1]",
|
| 60 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_q_lora_down",
|
| 61 |
+
"type" : "State"
|
| 62 |
+
},
|
| 63 |
+
{
|
| 64 |
+
"dataType" : "Float16",
|
| 65 |
+
"isOptional" : "0",
|
| 66 |
+
"formattedType" : "State (Float16 320 × 48 × 1 × 1)",
|
| 67 |
+
"shortDescription" : "",
|
| 68 |
+
"shape" : "[320, 48, 1, 1]",
|
| 69 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_q_lora_up",
|
| 70 |
+
"type" : "State"
|
| 71 |
+
},
|
| 72 |
+
{
|
| 73 |
+
"dataType" : "Float16",
|
| 74 |
+
"isOptional" : "0",
|
| 75 |
+
"formattedType" : "State (Float16 48 × 320 × 1 × 1)",
|
| 76 |
+
"shortDescription" : "",
|
| 77 |
+
"shape" : "[48, 320, 1, 1]",
|
| 78 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_k_lora_down",
|
| 79 |
+
"type" : "State"
|
| 80 |
+
},
|
| 81 |
+
{
|
| 82 |
+
"dataType" : "Float16",
|
| 83 |
+
"isOptional" : "0",
|
| 84 |
+
"formattedType" : "State (Float16 320 × 48 × 1 × 1)",
|
| 85 |
+
"shortDescription" : "",
|
| 86 |
+
"shape" : "[320, 48, 1, 1]",
|
| 87 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_k_lora_up",
|
| 88 |
+
"type" : "State"
|
| 89 |
+
},
|
| 90 |
+
{
|
| 91 |
+
"dataType" : "Float16",
|
| 92 |
+
"isOptional" : "0",
|
| 93 |
+
"formattedType" : "State (Float16 48 × 320 × 1 × 1)",
|
| 94 |
+
"shortDescription" : "",
|
| 95 |
+
"shape" : "[48, 320, 1, 1]",
|
| 96 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_v_lora_down",
|
| 97 |
+
"type" : "State"
|
| 98 |
+
},
|
| 99 |
+
{
|
| 100 |
+
"dataType" : "Float16",
|
| 101 |
+
"isOptional" : "0",
|
| 102 |
+
"formattedType" : "State (Float16 320 × 48 × 1 × 1)",
|
| 103 |
+
"shortDescription" : "",
|
| 104 |
+
"shape" : "[320, 48, 1, 1]",
|
| 105 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_v_lora_up",
|
| 106 |
+
"type" : "State"
|
| 107 |
+
},
|
| 108 |
+
{
|
| 109 |
+
"dataType" : "Float16",
|
| 110 |
+
"isOptional" : "0",
|
| 111 |
+
"formattedType" : "State (Float16 48 × 320 × 1 × 1)",
|
| 112 |
+
"shortDescription" : "",
|
| 113 |
+
"shape" : "[48, 320, 1, 1]",
|
| 114 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_out_0_lora_down",
|
| 115 |
+
"type" : "State"
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"dataType" : "Float16",
|
| 119 |
+
"isOptional" : "0",
|
| 120 |
+
"formattedType" : "State (Float16 320 × 48 × 1 × 1)",
|
| 121 |
+
"shortDescription" : "",
|
| 122 |
+
"shape" : "[320, 48, 1, 1]",
|
| 123 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn1_to_out_0_lora_up",
|
| 124 |
+
"type" : "State"
|
| 125 |
+
},
|
| 126 |
+
{
|
| 127 |
+
"dataType" : "Float16",
|
| 128 |
+
"isOptional" : "0",
|
| 129 |
+
"formattedType" : "State (Float16 48 × 320 × 1 × 1)",
|
| 130 |
+
"shortDescription" : "",
|
| 131 |
+
"shape" : "[48, 320, 1, 1]",
|
| 132 |
+
"name" : "down_blocks_0_attentions_0_transformer_blocks_0_attn2_to_q_lora_down",
|
| 133 |
+
"type" : "State"
|
| 134 |
+
},
|
| 135 |
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{
|
| 136 |
+
"dataType" : "Float16",
|
| 137 |
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| 1 |
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| 2 |
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