whisperkittools-a8c3cdeab8da5d76a7b952aa74ffebfbcd44804b 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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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", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
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 {
     func main<ios16>(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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openai_whisper-tiny.en/MelSpectrogram.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", "2.2.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.1"}})]
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 {
     func main<ios16>(tensor<fp16, [480000]> audio) {
             tensor<int32, [3]> var_10 = const()[name = tensor<string, []>("op_10"), val = tensor<int32, [3]>([1, 1, 480000])];

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

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 program(1.0)
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 {
     func main<ios16>(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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