Delete nvidia_parakeet-ja/MultimodalLogits.mlmodelc

nvidia_parakeet-ja/MultimodalLogits.mlmodelc/analytics/coremldata.bin

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-size 243

nvidia_parakeet-ja/MultimodalLogits.mlmodelc/coremldata.bin

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nvidia_parakeet-ja/MultimodalLogits.mlmodelc/metadata.json

@@ -1,85 +0,0 @@
-[
-  {
-    "metadataOutputVersion" : "3.0",
-    "storagePrecision" : "Float16",
-    "outputSchema" : [
-      {
-        "hasShapeFlexibility" : "0",
-        "isOptional" : "0",
-        "dataType" : "Float16",
-        "formattedType" : "MultiArray (Float16 1 × 3078)",
-        "shortDescription" : "",
-        "shape" : "[1, 3078]",
-        "name" : "raw_logits",
-        "type" : "MultiArray"
-      },
-      {
-        "hasShapeFlexibility" : "0",
-        "isOptional" : "0",
-        "dataType" : "Float16",
-        "formattedType" : "MultiArray (Float16 1 × 3078)",
-        "shortDescription" : "",
-        "shape" : "[1, 3078]",
-        "name" : "logits",
-        "type" : "MultiArray"
-      }
-    ],
-    "modelParameters" : [
-
-    ],
-    "specificationVersion" : 8,
-    "mlProgramOperationTypeHistogram" : {
-      "Ios16.softmax" : 1,
-      "Ios17.log" : 1,
-      "Ios17.linear" : 1,
-      "Ios17.add" : 1,
-      "Ios16.relu" : 1
-    },
-    "computePrecision" : "Mixed (Float16, Float32, Int32)",
-    "isUpdatable" : "0",
-    "stateSchema" : [
-
-    ],
-    "availability" : {
-      "macOS" : "14.0",
-      "tvOS" : "17.0",
-      "visionOS" : "1.0",
-      "watchOS" : "10.0",
-      "iOS" : "17.0",
-      "macCatalyst" : "17.0"
-    },
-    "modelType" : {
-      "name" : "MLModelType_mlProgram"
-    },
-    "userDefinedMetadata" : {
-      "com.github.apple.coremltools.conversion_date" : "2026-04-10",
-      "com.github.apple.coremltools.source" : "torch==2.11.0",
-      "com.github.apple.coremltools.version" : "9.0",
-      "com.github.apple.coremltools.source_dialect" : "TorchScript"
-    },
-    "inputSchema" : [
-      {
-        "hasShapeFlexibility" : "0",
-        "isOptional" : "0",
-        "dataType" : "Float16",
-        "formattedType" : "MultiArray (Float16 1 × 640)",
-        "shortDescription" : "",
-        "shape" : "[1, 640]",
-        "name" : "encoder_output_projected",
-        "type" : "MultiArray"
-      },
-      {
-        "hasShapeFlexibility" : "0",
-        "isOptional" : "0",
-        "dataType" : "Float16",
-        "formattedType" : "MultiArray (Float16 1 × 640)",
-        "shortDescription" : "",
-        "shape" : "[1, 640]",
-        "name" : "decoder_output_projected",
-        "type" : "MultiArray"
-      }
-    ],
-    "generatedClassName" : "MultimodalLogits",
-    "method" : "predict"
-  }
-]

nvidia_parakeet-ja/MultimodalLogits.mlmodelc/model.mil

@@ -1,15 +0,0 @@
-program(1.0)
-[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3404.16.1"}, {"coremlc-version", "3404.23.1"}, {"coremltools-component-torch", "2.11.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
-{
-    func main<ios17>(tensor<fp16, [1, 640]> decoder_output_projected, tensor<fp16, [1, 640]> encoder_output_projected) {
-            tensor<fp16, [1, 640]> input_1_cast_fp16 = add(x = decoder_output_projected, y = encoder_output_projected)[name = tensor<string, []>("input_1_cast_fp16")];
-            tensor<fp16, [1, 640]> input_3_cast_fp16 = relu(x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
-            tensor<fp16, [3078, 640]> joint_net_1_weight_to_fp16 = const()[name = tensor<string, []>("joint_net_1_weight_to_fp16"), val = tensor<fp16, [3078, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
-            tensor<fp16, [3078]> joint_net_1_bias_to_fp16 = const()[name = tensor<string, []>("joint_net_1_bias_to_fp16"), val = tensor<fp16, [3078]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3939968)))];
-            tensor<fp16, [1, 3078]> raw_logits = linear(bias = joint_net_1_bias_to_fp16, weight = joint_net_1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
-            tensor<int32, []> var_11 = const()[name = tensor<string, []>("op_11"), val = tensor<int32, []>(-1)];
-            tensor<fp16, [1, 3078]> var_13_softmax_cast_fp16 = softmax(axis = var_11, x = raw_logits)[name = tensor<string, []>("op_13_softmax_cast_fp16")];
-            tensor<fp32, []> var_13_epsilon_0 = const()[name = tensor<string, []>("op_13_epsilon_0"), val = tensor<fp32, []>(0x1p-149)];
-            tensor<fp16, [1, 3078]> logits = log(epsilon = var_13_epsilon_0, x = var_13_softmax_cast_fp16)[name = tensor<string, []>("op_13_cast_fp16")];
-        } -> (raw_logits, logits);
-}

nvidia_parakeet-ja/MultimodalLogits.mlmodelc/weights/weight.bin

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