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[
{
"shortDescription" : "This is a model that can be used to generate and modify images based on text prompts.It is a Latent Diffusion Model that uses two fixed, pretrained text encoders (OpenCLIP-ViT\/G and CLIP-ViT\/L).Please refer to https:\/\/arxiv.org\/abs\/2307.01952 for details",
"metadataOutputVersion" : "3.0",
"outputSchema" : [
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float32",
"formattedType" : "MultiArray (Float32)",
"shortDescription" : "Same shape and dtype as the `sample` input. The predicted noise to facilitate the reverse diffusion (denoising) process",
"shape" : "[]",
"name" : "noise_pred",
"type" : "MultiArray"
}
],
"version" : "stabilityai\/stable-diffusion-xl-base-0.9",
"modelParameters" : [
],
"author" : "Please refer to the Model Card available at huggingface.co\/stabilityai\/stable-diffusion-xl-base-0.9",
"specificationVersion" : 7,
"storagePrecision" : "Float16",
"license" : "Please refer to the Model Card available at huggingface.co\/stabilityai\/stable-diffusion-xl-base-0.9\/blob\/main\/LICENSE.md",
"mlProgramOperationTypeHistogram" : {
"UpsampleNearestNeighbor" : 2,
"Ios16.reduceMean" : 512,
"Ios16.sin" : 2,
"Ios16.softmax" : 140,
"Split" : 70,
"Ios16.add" : 722,
"Concat" : 14,
"Ios16.realDiv" : 46,
"Ios16.square" : 46,
"ExpandDims" : 6,
"Ios16.sub" : 256,
"Ios16.cast" : 1,
"Ios16.conv" : 794,
"Ios16.constexprLutToDense" : 870,
"Ios16.gelu" : 70,
"Ios16.matmul" : 280,
"Ios16.batchNorm" : 46,
"Ios16.reshape" : 676,
"Ios16.rsqrt" : 210,
"Ios16.silu" : 38,
"Ios16.sqrt" : 46,
"Ios16.mul" : 842,
"Ios16.cos" : 2,
"SliceByIndex" : 4
},
"computePrecision" : "Mixed (Float32, Float16, Int32)",
"isUpdatable" : "0",
"availability" : {
"macOS" : "13.0",
"tvOS" : "16.0",
"watchOS" : "9.0",
"iOS" : "16.0",
"macCatalyst" : "16.0"
},
"modelType" : {
"name" : "MLModelType_mlProgram"
},
"inputSchema" : [
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float16",
"formattedType" : "MultiArray (Float16 2 × 4 × 128 × 128)",
"shortDescription" : "The low resolution latent feature maps being denoised through reverse diffusion",
"shape" : "[2, 4, 128, 128]",
"name" : "sample",
"type" : "MultiArray"
},
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float16",
"formattedType" : "MultiArray (Float16 2)",
"shortDescription" : "A value emitted by the associated scheduler object to condition the model on a given noise schedule",
"shape" : "[2]",
"name" : "timestep",
"type" : "MultiArray"
},
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float16",
"formattedType" : "MultiArray (Float16 2 × 2048 × 1 × 77)",
"shortDescription" : "Output embeddings from the associated text_encoder model to condition to generated image on text. A maximum of 77 tokens (~40 words) are allowed. Longer text is truncated. Shorter text does not reduce computation.",
"shape" : "[2, 2048, 1, 77]",
"name" : "encoder_hidden_states",
"type" : "MultiArray"
},
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float16",
"formattedType" : "MultiArray (Float16 2 × 1280)",
"shortDescription" : "Additional embeddings passed to the unet based on the pooled output of the text encoders.",
"shape" : "[2, 1280]",
"name" : "text_embeds",
"type" : "MultiArray"
},
{
"hasShapeFlexibility" : "0",
"isOptional" : "0",
"dataType" : "Float16",
"formattedType" : "MultiArray (Float16 2 × 6)",
"shortDescription" : "Additional embeddings passed to the unet based on width and height dimensions.For SDXL, default values look like [1024, 1024, 0, 0, 1024, 1024]",
"shape" : "[2, 6]",
"name" : "time_ids",
"type" : "MultiArray"
}
],
"userDefinedMetadata" : {
"com.github.apple.coremltools.version" : "7.0b1",
"com.github.apple.coremltools.source" : "torch==2.1.0.dev20230718",
"com.github.apple.ml-stable-diffusion.version" : "1.0.0"
},
"generatedClassName" : "Stable_Diffusion_version_stabilityai_stable_diffusion_xl_base_0_9_unet",
"method" : "predict"
}
]