whisperkittools-539b2f3b441b2ce4bba6be007f460017b5ca6796 generated files: openai_whisper-tiny.en

openai_whisper-tiny.en/AudioEncoder.mlmodelc/analytics/coremldata.bin

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openai_whisper-tiny.en/AudioEncoder.mlmodelc/coremldata.bin

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openai_whisper-tiny.en/AudioEncoder.mlmodelc/metadata.json

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-      "com.github.apple.coremltools.source" : "torch==2.1.2",
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openai_whisper-tiny.en/AudioEncoder.mlmodelc/model.mil

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 program(1.0)
-[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.1.2"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
+[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
 {
     func main<ios17>(tensor<fp16, [1, 80, 1, 3000]> melspectrogram_features) {
             tensor<int32, [2]> var_34 = const()[name = tensor<string, []>("op_34"), val = tensor<int32, [2]>([1, 1])];

openai_whisper-tiny.en/AudioEncoder.mlmodelc/weights/weight.bin

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openai_whisper-tiny.en/MelSpectrogram.mlmodelc/analytics/coremldata.bin

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openai_whisper-tiny.en/MelSpectrogram.mlmodelc/coremldata.bin

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openai_whisper-tiny.en/MelSpectrogram.mlmodelc/metadata.json

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     },
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       "com.github.apple.coremltools.source_dialect" : "TorchScript",
-      "com.github.apple.coremltools.source" : "torch==2.1.2",
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     },
     "inputSchema" : [

openai_whisper-tiny.en/MelSpectrogram.mlmodelc/model.mil

@@ -1,15 +1,15 @@
 program(1.0)
-[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.1.2"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
+[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
 {
     func main<ios17>(tensor<fp16, [480000]> audio) {
             tensor<int32, [3]> var_10 = const()[name = tensor<string, []>("op_10"), val = tensor<int32, [3]>([1, 1, 480000])];
-            tensor<fp16, [1, 1, 480000]> var_11_cast_fp16 = reshape(shape = var_10, x = audio)[name = tensor<string, []>("op_11_cast_fp16")];
-            tensor<int32, [6]> input_1_pad_0 = const()[name = tensor<string, []>("input_1_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 200, 200])];
-            tensor<string, []> input_1_mode_0 = const()[name = tensor<string, []>("input_1_mode_0"), val = tensor<string, []>("reflect")];
-            tensor<fp16, []> input_1_constant_val_0_to_fp16 = const()[name = tensor<string, []>("input_1_constant_val_0_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
-            tensor<fp16, [1, 1, 480400]> input_1_cast_fp16 = pad(constant_val = input_1_constant_val_0_to_fp16, mode = input_1_mode_0, pad = input_1_pad_0, x = var_11_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")];
+            tensor<fp16, [1, 1, 480000]> input_1_cast_fp16 = reshape(shape = var_10, x = audio)[name = tensor<string, []>("input_1_cast_fp16")];
+            tensor<int32, [6]> input_3_pad_0 = const()[name = tensor<string, []>("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 200, 200])];
+            tensor<string, []> input_3_mode_0 = const()[name = tensor<string, []>("input_3_mode_0"), val = tensor<string, []>("reflect")];
+            tensor<fp16, []> input_3_constant_val_0_to_fp16 = const()[name = tensor<string, []>("input_3_constant_val_0_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
+            tensor<fp16, [1, 1, 480400]> input_3_cast_fp16 = pad(constant_val = input_3_constant_val_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
             tensor<int32, [1]> var_22 = const()[name = tensor<string, []>("op_22"), val = tensor<int32, [1]>([480400])];
-            tensor<fp16, [480400]> input_cast_fp16 = reshape(shape = var_22, x = input_1_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
+            tensor<fp16, [480400]> input_cast_fp16 = reshape(shape = var_22, x = input_3_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
             tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = tensor<string, []>("expand_dims_0_axes_0"), val = tensor<int32, [1]>([0])];
             tensor<fp16, [1, 480400]> expand_dims_0_cast_fp16 = expand_dims(axes = expand_dims_0_axes_0, x = input_cast_fp16)[name = tensor<string, []>("expand_dims_0_cast_fp16")];
             tensor<int32, [1]> expand_dims_3 = const()[name = tensor<string, []>("expand_dims_3"), val = tensor<int32, [1]>([160])];

openai_whisper-tiny.en/MelSpectrogram.mlmodelc/weights/weight.bin

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openai_whisper-tiny.en/TextDecoder.mlmodelc/analytics/coremldata.bin

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openai_whisper-tiny.en/TextDecoder.mlmodelc/coremldata.bin

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openai_whisper-tiny.en/TextDecoder.mlmodelc/metadata.json

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     },
     "userDefinedMetadata" : {
       "com.github.apple.coremltools.source_dialect" : "TorchScript",
-      "com.github.apple.coremltools.source" : "torch==2.1.2",
+      "com.github.apple.coremltools.source" : "torch==2.2.0",
       "com.github.apple.coremltools.version" : "7.1"
     },
     "inputSchema" : [

openai_whisper-tiny.en/TextDecoder.mlmodelc/model.mil

@@ -1,5 +1,5 @@
 program(1.0)
-[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.1.2"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
+[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.3"}, {"coremltools-component-torch", "2.2.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
 {
     func main<ios17>(tensor<int32, [1]> cache_length, tensor<fp16, [1, 448]> decoder_key_padding_mask, tensor<fp16, [1, 384, 1, 1500]> encoder_output_embeds, tensor<int32, [1]> input_ids, tensor<fp16, [1, 1536, 1, 448]> key_cache, tensor<fp16, [1, 448]> kv_cache_update_mask, tensor<fp16, [1, 1536, 1, 448]> value_cache) {
             tensor<int32, []> var_24_axis_0 = const()[name = tensor<string, []>("op_24_axis_0"), val = tensor<int32, []>(0)];

openai_whisper-tiny.en/TextDecoder.mlmodelc/weights/weight.bin

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