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[
{
"shortDescription" : "Stable Diffusion generates images conditioned on text and\/or other images as input through the diffusion process. Please refer to https:\/\/arxiv.org\/abs\/2112.10752 for details.",
"metadataOutputVersion" : "3.0",
"outputSchema" : [
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float32",
"formattedType" : "MultiArray (Float32 1 × 8 × 64 × 64)",
"shortDescription" : "The latent embeddings from the unet model from the input image.",
"shape" : "[1, 8, 64, 64]",
"name" : "latent",
"type" : "MultiArray"
}
],
"version" : "Lykon\/dreamshaper-8-lcm",
"modelParameters" : [
],
"author" : "Please refer to the Model Card available at huggingface.co\/Lykon\/dreamshaper-8-lcm",
"specificationVersion" : 7,
"storagePrecision" : "Float16",
"license" : "OpenRAIL (https:\/\/huggingface.co\/spaces\/CompVis\/stable-diffusion-license)",
"mlProgramOperationTypeHistogram" : {
"Pad" : 3,
"Ios16.cast" : 1,
"Ios16.mul" : 2,
"Ios16.sqrt" : 22,
"Ios16.sub" : 22,
"Transpose" : 6,
"Ios16.conv" : 28,
"Ios16.add" : 34,
"Ios16.linear" : 4,
"Ios16.matmul" : 2,
"Ios16.realDiv" : 22,
"Ios16.reduceMean" : 44,
"Ios16.softmax" : 1,
"Ios16.batchNorm" : 21,
"Ios16.square" : 22,
"Ios16.reshape" : 49,
"Ios16.silu" : 21
},
"computePrecision" : "Mixed (Float16, Float32, Int32)",
"isUpdatable" : "0",
"availability" : {
"macOS" : "13.0",
"tvOS" : "16.0",
"visionOS" : "1.0",
"watchOS" : "9.0",
"iOS" : "16.0",
"macCatalyst" : "16.0"
},
"modelType" : {
"name" : "MLModelType_mlProgram"
},
"inputSchema" : [
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float16",
"formattedType" : "MultiArray (Float16 1 × 3 × 512 × 512)",
"shortDescription" : "The input image to base the initial latents on normalized to range [-1, 1]",
"shape" : "[1, 3, 512, 512]",
"name" : "x",
"type" : "MultiArray"
}
],
"userDefinedMetadata" : {
"com.github.apple.coremltools.version" : "7.0b2",
"com.github.apple.coremltools.source" : "torch==2.0.0"
},
"generatedClassName" : "Stable_Diffusion_version_Lykon_dreamshaper_8_lcm_vae_encoder",
"method" : "predict"
}
]