aotrih commited on
Commit
efa763b
1 Parent(s): 161d59a

whisperkittools-192190cedeefc4d317d13c2196dc29f9a9f99628 generated files: openai_whisper-tiny.en

Browse files
openai_whisper-tiny.en/AudioEncoder.mlmodelc/analytics/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0b25820e5b2ab0b0686b4bea147fb217d1d1bface45170ff4ffde01fa6864ae2
3
+ size 243
openai_whisper-tiny.en/AudioEncoder.mlmodelc/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:142c33ade402fe41952059f175eb855093dfe09b5d2b84624a31e3a9952ed47d
3
+ size 347
openai_whisper-tiny.en/AudioEncoder.mlmodelc/metadata.json ADDED
@@ -0,0 +1,69 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "metadataOutputVersion" : "3.0",
4
+ "storagePrecision" : "Float16",
5
+ "outputSchema" : [
6
+ {
7
+ "hasShapeFlexibility" : "0",
8
+ "isOptional" : "0",
9
+ "dataType" : "Float16",
10
+ "formattedType" : "MultiArray (Float16 1 × 384 × 1 × 1500)",
11
+ "shortDescription" : "",
12
+ "shape" : "[1, 384, 1, 1500]",
13
+ "name" : "encoder_output_embeds",
14
+ "type" : "MultiArray"
15
+ }
16
+ ],
17
+ "modelParameters" : [
18
+
19
+ ],
20
+ "specificationVersion" : 7,
21
+ "mlProgramOperationTypeHistogram" : {
22
+ "Concat" : 28,
23
+ "Ios16.rsqrt" : 9,
24
+ "Ios16.mul" : 114,
25
+ "SliceByIndex" : 168,
26
+ "Ios16.sub" : 9,
27
+ "Transpose" : 4,
28
+ "Ios16.einsum" : 192,
29
+ "Ios16.conv" : 26,
30
+ "Ios16.add" : 18,
31
+ "Ios16.reduceMean" : 18,
32
+ "Ios16.softmax" : 96,
33
+ "Ios16.gelu" : 6,
34
+ "Ios16.batchNorm" : 9
35
+ },
36
+ "computePrecision" : "Mixed (Float16, Int32)",
37
+ "isUpdatable" : "0",
38
+ "availability" : {
39
+ "macOS" : "13.0",
40
+ "tvOS" : "16.0",
41
+ "visionOS" : "1.0",
42
+ "watchOS" : "9.0",
43
+ "iOS" : "16.0",
44
+ "macCatalyst" : "16.0"
45
+ },
46
+ "modelType" : {
47
+ "name" : "MLModelType_mlProgram"
48
+ },
49
+ "userDefinedMetadata" : {
50
+ "com.github.apple.coremltools.source_dialect" : "TorchScript",
51
+ "com.github.apple.coremltools.source" : "torch==2.2.1",
52
+ "com.github.apple.coremltools.version" : "7.1"
53
+ },
54
+ "inputSchema" : [
55
+ {
56
+ "hasShapeFlexibility" : "0",
57
+ "isOptional" : "0",
58
+ "dataType" : "Float16",
59
+ "formattedType" : "MultiArray (Float16 1 × 80 × 1 × 3000)",
60
+ "shortDescription" : "",
61
+ "shape" : "[1, 80, 1, 3000]",
62
+ "name" : "melspectrogram_features",
63
+ "type" : "MultiArray"
64
+ }
65
+ ],
66
+ "generatedClassName" : "AudioEncoder",
67
+ "method" : "predict"
68
+ }
69
+ ]
openai_whisper-tiny.en/AudioEncoder.mlmodelc/model.mil ADDED
The diff for this file is too large to render. See raw diff
 
openai_whisper-tiny.en/AudioEncoder.mlmodelc/weights/weight.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d5dd3d07ebd9f09e1f4d2cb5e723b7507370a2239cdded9a5375628ed7e1be88
3
+ size 16422784
openai_whisper-tiny.en/MelSpectrogram.mlmodelc/analytics/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7f77e6457285248f99cd7aa3fd4cc2efbb17733e63e7023ac53abe1f95785d07
3
+ size 243
openai_whisper-tiny.en/MelSpectrogram.mlmodelc/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dabdc5aa69f6ef4d97dc9499f5c30514e00e96b53b750b33a5a6471363c71662
3
+ size 328
openai_whisper-tiny.en/MelSpectrogram.mlmodelc/metadata.json ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "metadataOutputVersion" : "3.0",
4
+ "storagePrecision" : "Float16",
5
+ "outputSchema" : [
6
+ {
7
+ "hasShapeFlexibility" : "0",
8
+ "isOptional" : "0",
9
+ "dataType" : "Float16",
10
+ "formattedType" : "MultiArray (Float16 1 × 80 × 1 × 3000)",
11
+ "shortDescription" : "",
12
+ "shape" : "[1, 80, 1, 3000]",
13
+ "name" : "melspectrogram_features",
14
+ "type" : "MultiArray"
15
+ }
16
+ ],
17
+ "modelParameters" : [
18
+
19
+ ],
20
+ "specificationVersion" : 7,
21
+ "mlProgramOperationTypeHistogram" : {
22
+ "Pad" : 1,
23
+ "Ios16.mul" : 2,
24
+ "SliceByIndex" : 1,
25
+ "Ios16.sub" : 1,
26
+ "Ios16.log" : 1,
27
+ "Ios16.conv" : 2,
28
+ "Ios16.add" : 3,
29
+ "Ios16.square" : 2,
30
+ "Ios16.matmul" : 1,
31
+ "Squeeze" : 2,
32
+ "Ios16.maximum" : 1,
33
+ "ExpandDims" : 4,
34
+ "Ios16.reduceMax" : 1,
35
+ "Identity" : 1,
36
+ "Ios16.reshape" : 2
37
+ },
38
+ "computePrecision" : "Mixed (Float16, Int32)",
39
+ "isUpdatable" : "0",
40
+ "availability" : {
41
+ "macOS" : "13.0",
42
+ "tvOS" : "16.0",
43
+ "visionOS" : "1.0",
44
+ "watchOS" : "9.0",
45
+ "iOS" : "16.0",
46
+ "macCatalyst" : "16.0"
47
+ },
48
+ "modelType" : {
49
+ "name" : "MLModelType_mlProgram"
50
+ },
51
+ "userDefinedMetadata" : {
52
+ "com.github.apple.coremltools.source_dialect" : "TorchScript",
53
+ "com.github.apple.coremltools.version" : "7.1",
54
+ "com.github.apple.coremltools.source" : "torch==2.2.1"
55
+ },
56
+ "inputSchema" : [
57
+ {
58
+ "hasShapeFlexibility" : "0",
59
+ "isOptional" : "0",
60
+ "dataType" : "Float16",
61
+ "formattedType" : "MultiArray (Float16 480000)",
62
+ "shortDescription" : "",
63
+ "shape" : "[480000]",
64
+ "name" : "audio",
65
+ "type" : "MultiArray"
66
+ }
67
+ ],
68
+ "generatedClassName" : "MelSpectrogram",
69
+ "method" : "predict"
70
+ }
71
+ ]
openai_whisper-tiny.en/MelSpectrogram.mlmodelc/model.mil ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ program(1.0)
2
+ [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"}})]
3
+ {
4
+ func main<ios16>(tensor<fp16, [480000]> audio) {
5
+ tensor<int32, [3]> var_10 = const()[name = tensor<string, []>("op_10"), val = tensor<int32, [3]>([1, 1, 480000])];
6
+ tensor<fp16, [1, 1, 480000]> input_1_cast_fp16 = reshape(shape = var_10, x = audio)[name = tensor<string, []>("input_1_cast_fp16")];
7
+ 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])];
8
+ tensor<string, []> input_3_mode_0 = const()[name = tensor<string, []>("input_3_mode_0"), val = tensor<string, []>("reflect")];
9
+ 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)];
10
+ 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")];
11
+ tensor<int32, [1]> var_22 = const()[name = tensor<string, []>("op_22"), val = tensor<int32, [1]>([480400])];
12
+ tensor<fp16, [480400]> input_cast_fp16 = reshape(shape = var_22, x = input_3_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
13
+ tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = tensor<string, []>("expand_dims_0_axes_0"), val = tensor<int32, [1]>([0])];
14
+ 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")];
15
+ tensor<int32, [1]> expand_dims_3 = const()[name = tensor<string, []>("expand_dims_3"), val = tensor<int32, [1]>([160])];
16
+ tensor<int32, [1]> expand_dims_4_axes_0 = const()[name = tensor<string, []>("expand_dims_4_axes_0"), val = tensor<int32, [1]>([1])];
17
+ tensor<fp16, [1, 1, 480400]> expand_dims_4_cast_fp16 = expand_dims(axes = expand_dims_4_axes_0, x = expand_dims_0_cast_fp16)[name = tensor<string, []>("expand_dims_4_cast_fp16")];
18
+ tensor<string, []> conv_0_pad_type_0 = const()[name = tensor<string, []>("conv_0_pad_type_0"), val = tensor<string, []>("valid")];
19
+ tensor<int32, [2]> conv_0_pad_0 = const()[name = tensor<string, []>("conv_0_pad_0"), val = tensor<int32, [2]>([0, 0])];
20
+ tensor<int32, [1]> conv_0_dilations_0 = const()[name = tensor<string, []>("conv_0_dilations_0"), val = tensor<int32, [1]>([1])];
21
+ tensor<int32, []> conv_0_groups_0 = const()[name = tensor<string, []>("conv_0_groups_0"), val = tensor<int32, []>(1)];
22
+ tensor<fp16, [201, 1, 400]> expand_dims_1_to_fp16 = const()[name = tensor<string, []>("expand_dims_1_to_fp16"), val = tensor<fp16, [201, 1, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
23
+ tensor<fp16, [1, 201, 3001]> conv_0_cast_fp16 = conv(dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = expand_dims_3, weight = expand_dims_1_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor<string, []>("conv_0_cast_fp16")];
24
+ tensor<string, []> conv_1_pad_type_0 = const()[name = tensor<string, []>("conv_1_pad_type_0"), val = tensor<string, []>("valid")];
25
+ tensor<int32, [2]> conv_1_pad_0 = const()[name = tensor<string, []>("conv_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
26
+ tensor<int32, [1]> conv_1_dilations_0 = const()[name = tensor<string, []>("conv_1_dilations_0"), val = tensor<int32, [1]>([1])];
27
+ tensor<int32, []> conv_1_groups_0 = const()[name = tensor<string, []>("conv_1_groups_0"), val = tensor<int32, []>(1)];
28
+ tensor<fp16, [201, 1, 400]> expand_dims_2_to_fp16 = const()[name = tensor<string, []>("expand_dims_2_to_fp16"), val = tensor<fp16, [201, 1, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160960)))];
29
+ tensor<fp16, [1, 201, 3001]> conv_1_cast_fp16 = conv(dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = expand_dims_3, weight = expand_dims_2_to_fp16, x = expand_dims_4_cast_fp16)[name = tensor<string, []>("conv_1_cast_fp16")];
30
+ tensor<int32, [1]> squeeze_0_axes_0 = const()[name = tensor<string, []>("squeeze_0_axes_0"), val = tensor<int32, [1]>([0])];
31
+ tensor<fp16, [201, 3001]> squeeze_0_cast_fp16 = squeeze(axes = squeeze_0_axes_0, x = conv_0_cast_fp16)[name = tensor<string, []>("squeeze_0_cast_fp16")];
32
+ tensor<int32, [1]> squeeze_1_axes_0 = const()[name = tensor<string, []>("squeeze_1_axes_0"), val = tensor<int32, [1]>([0])];
33
+ tensor<fp16, [201, 3001]> squeeze_1_cast_fp16 = squeeze(axes = squeeze_1_axes_0, x = conv_1_cast_fp16)[name = tensor<string, []>("squeeze_1_cast_fp16")];
34
+ tensor<fp16, [201, 3001]> square_0_cast_fp16 = square(x = squeeze_0_cast_fp16)[name = tensor<string, []>("square_0_cast_fp16")];
35
+ tensor<fp16, [201, 3001]> square_1_cast_fp16 = square(x = squeeze_1_cast_fp16)[name = tensor<string, []>("square_1_cast_fp16")];
36
+ tensor<fp16, [201, 3001]> add_1_cast_fp16 = add(x = square_0_cast_fp16, y = square_1_cast_fp16)[name = tensor<string, []>("add_1_cast_fp16")];
37
+ tensor<fp16, [201, 3001]> magnitudes_1_cast_fp16 = identity(x = add_1_cast_fp16)[name = tensor<string, []>("magnitudes_1_cast_fp16")];
38
+ tensor<int32, [2]> magnitudes_begin_0 = const()[name = tensor<string, []>("magnitudes_begin_0"), val = tensor<int32, [2]>([0, 0])];
39
+ tensor<int32, [2]> magnitudes_end_0 = const()[name = tensor<string, []>("magnitudes_end_0"), val = tensor<int32, [2]>([201, 3000])];
40
+ tensor<bool, [2]> magnitudes_end_mask_0 = const()[name = tensor<string, []>("magnitudes_end_mask_0"), val = tensor<bool, [2]>([true, false])];
41
+ tensor<fp16, [201, 3000]> magnitudes_cast_fp16 = slice_by_index(begin = magnitudes_begin_0, end = magnitudes_end_0, end_mask = magnitudes_end_mask_0, x = magnitudes_1_cast_fp16)[name = tensor<string, []>("magnitudes_cast_fp16")];
42
+ tensor<bool, []> mel_spec_1_transpose_x_0 = const()[name = tensor<string, []>("mel_spec_1_transpose_x_0"), val = tensor<bool, []>(false)];
43
+ tensor<bool, []> mel_spec_1_transpose_y_0 = const()[name = tensor<string, []>("mel_spec_1_transpose_y_0"), val = tensor<bool, []>(false)];
44
+ tensor<fp16, [80, 201]> mel_filters_to_fp16 = const()[name = tensor<string, []>("mel_filters_to_fp16"), val = tensor<fp16, [80, 201]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(321856)))];
45
+ tensor<fp16, [80, 3000]> mel_spec_1_cast_fp16 = matmul(transpose_x = mel_spec_1_transpose_x_0, transpose_y = mel_spec_1_transpose_y_0, x = mel_filters_to_fp16, y = magnitudes_cast_fp16)[name = tensor<string, []>("mel_spec_1_cast_fp16")];
46
+ tensor<fp16, []> var_41_to_fp16 = const()[name = tensor<string, []>("op_41_to_fp16"), val = tensor<fp16, []>(0x1p-24)];
47
+ tensor<fp16, [80, 3000]> mel_spec_cast_fp16 = add(x = mel_spec_1_cast_fp16, y = var_41_to_fp16)[name = tensor<string, []>("mel_spec_cast_fp16")];
48
+ tensor<fp16, []> log_0_epsilon_0_to_fp16 = const()[name = tensor<string, []>("log_0_epsilon_0_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
49
+ tensor<fp16, [80, 3000]> log_0_cast_fp16 = log(epsilon = log_0_epsilon_0_to_fp16, x = mel_spec_cast_fp16)[name = tensor<string, []>("log_0_cast_fp16")];
50
+ tensor<fp16, []> mul_0_y_0_to_fp16 = const()[name = tensor<string, []>("mul_0_y_0_to_fp16"), val = tensor<fp16, []>(0x1.bccp-2)];
51
+ tensor<fp16, [80, 3000]> mul_0_cast_fp16 = mul(x = log_0_cast_fp16, y = mul_0_y_0_to_fp16)[name = tensor<string, []>("mul_0_cast_fp16")];
52
+ tensor<bool, []> var_44_keep_dims_0 = const()[name = tensor<string, []>("op_44_keep_dims_0"), val = tensor<bool, []>(false)];
53
+ tensor<fp16, []> var_44_cast_fp16 = reduce_max(keep_dims = var_44_keep_dims_0, x = mul_0_cast_fp16)[name = tensor<string, []>("op_44_cast_fp16")];
54
+ tensor<fp16, []> var_46_to_fp16 = const()[name = tensor<string, []>("op_46_to_fp16"), val = tensor<fp16, []>(0x1p+3)];
55
+ tensor<fp16, []> var_47_cast_fp16 = sub(x = var_44_cast_fp16, y = var_46_to_fp16)[name = tensor<string, []>("op_47_cast_fp16")];
56
+ tensor<fp16, [80, 3000]> log_spec_3_cast_fp16 = maximum(x = mul_0_cast_fp16, y = var_47_cast_fp16)[name = tensor<string, []>("log_spec_3_cast_fp16")];
57
+ tensor<fp16, []> var_50_to_fp16 = const()[name = tensor<string, []>("op_50_to_fp16"), val = tensor<fp16, []>(0x1p+2)];
58
+ tensor<fp16, [80, 3000]> var_51_cast_fp16 = add(x = log_spec_3_cast_fp16, y = var_50_to_fp16)[name = tensor<string, []>("op_51_cast_fp16")];
59
+ tensor<fp16, []> _inversed_log_spec_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_log_spec_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-2)];
60
+ tensor<fp16, [80, 3000]> _inversed_log_spec_cast_fp16 = mul(x = var_51_cast_fp16, y = _inversed_log_spec_y_0_to_fp16)[name = tensor<string, []>("_inversed_log_spec_cast_fp16")];
61
+ tensor<int32, [1]> var_55_axes_0 = const()[name = tensor<string, []>("op_55_axes_0"), val = tensor<int32, [1]>([0])];
62
+ tensor<fp16, [1, 80, 3000]> var_55_cast_fp16 = expand_dims(axes = var_55_axes_0, x = _inversed_log_spec_cast_fp16)[name = tensor<string, []>("op_55_cast_fp16")];
63
+ tensor<int32, [1]> var_62_axes_0 = const()[name = tensor<string, []>("op_62_axes_0"), val = tensor<int32, [1]>([2])];
64
+ tensor<fp16, [1, 80, 1, 3000]> melspectrogram_features = expand_dims(axes = var_62_axes_0, x = var_55_cast_fp16)[name = tensor<string, []>("op_62_cast_fp16")];
65
+ } -> (melspectrogram_features);
66
+ }
openai_whisper-tiny.en/MelSpectrogram.mlmodelc/weights/weight.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:45634c808d510c6cae6cc148354133aecc437612fe27d8df346f37ae302503eb
3
+ size 354080
openai_whisper-tiny.en/TextDecoder.mlmodelc/analytics/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9e18966f107bc33b55e2b449982028367637f37865b0775ae429334b3bc13160
3
+ size 243
openai_whisper-tiny.en/TextDecoder.mlmodelc/coremldata.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3d9ad3d15525ca0eabf507e4ea88fb19b6d8d5d09191c8eaddffe82c8042959
3
+ size 633
openai_whisper-tiny.en/TextDecoder.mlmodelc/metadata.json ADDED
@@ -0,0 +1,165 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [
2
+ {
3
+ "metadataOutputVersion" : "3.0",
4
+ "storagePrecision" : "Float16",
5
+ "outputSchema" : [
6
+ {
7
+ "hasShapeFlexibility" : "0",
8
+ "isOptional" : "0",
9
+ "dataType" : "Float16",
10
+ "formattedType" : "MultiArray (Float16 1 × 1 × 51864)",
11
+ "shortDescription" : "",
12
+ "shape" : "[1, 1, 51864]",
13
+ "name" : "logits",
14
+ "type" : "MultiArray"
15
+ },
16
+ {
17
+ "hasShapeFlexibility" : "0",
18
+ "isOptional" : "0",
19
+ "dataType" : "Float16",
20
+ "formattedType" : "MultiArray (Float16 1 × 1536 × 1 × 1)",
21
+ "shortDescription" : "",
22
+ "shape" : "[1, 1536, 1, 1]",
23
+ "name" : "key_cache_updates",
24
+ "type" : "MultiArray"
25
+ },
26
+ {
27
+ "hasShapeFlexibility" : "0",
28
+ "isOptional" : "0",
29
+ "dataType" : "Float16",
30
+ "formattedType" : "MultiArray (Float16 1 × 1536 × 1 × 1)",
31
+ "shortDescription" : "",
32
+ "shape" : "[1, 1536, 1, 1]",
33
+ "name" : "value_cache_updates",
34
+ "type" : "MultiArray"
35
+ },
36
+ {
37
+ "hasShapeFlexibility" : "0",
38
+ "isOptional" : "0",
39
+ "dataType" : "Float16",
40
+ "formattedType" : "MultiArray (Float16 1 × 1500)",
41
+ "shortDescription" : "",
42
+ "shape" : "[1, 1500]",
43
+ "name" : "alignment_heads_weights",
44
+ "type" : "MultiArray"
45
+ }
46
+ ],
47
+ "modelParameters" : [
48
+
49
+ ],
50
+ "specificationVersion" : 7,
51
+ "mlProgramOperationTypeHistogram" : {
52
+ "Split" : 2,
53
+ "Concat" : 3,
54
+ "Ios16.rsqrt" : 13,
55
+ "Ios16.mul" : 50,
56
+ "Squeeze" : 1,
57
+ "SliceByIndex" : 16,
58
+ "Ios16.sub" : 14,
59
+ "Transpose" : 1,
60
+ "Ios16.conv" : 40,
61
+ "Ios16.add" : 38,
62
+ "Ios16.linear" : 1,
63
+ "Ios16.matmul" : 16,
64
+ "Ios16.gelu" : 4,
65
+ "Ios16.reduceMean" : 27,
66
+ "ExpandDims" : 6,
67
+ "Ios16.batchNorm" : 13,
68
+ "Ios16.gather" : 2,
69
+ "Ios16.reshape" : 32,
70
+ "Ios16.softmax" : 8
71
+ },
72
+ "computePrecision" : "Mixed (Float16, Int32)",
73
+ "isUpdatable" : "0",
74
+ "availability" : {
75
+ "macOS" : "13.0",
76
+ "tvOS" : "16.0",
77
+ "visionOS" : "1.0",
78
+ "watchOS" : "9.0",
79
+ "iOS" : "16.0",
80
+ "macCatalyst" : "16.0"
81
+ },
82
+ "modelType" : {
83
+ "name" : "MLModelType_mlProgram"
84
+ },
85
+ "userDefinedMetadata" : {
86
+ "com.github.apple.coremltools.source_dialect" : "TorchScript",
87
+ "com.github.apple.coremltools.source" : "torch==2.2.1",
88
+ "com.github.apple.coremltools.version" : "7.1"
89
+ },
90
+ "inputSchema" : [
91
+ {
92
+ "hasShapeFlexibility" : "0",
93
+ "isOptional" : "0",
94
+ "dataType" : "Int32",
95
+ "formattedType" : "MultiArray (Int32 1)",
96
+ "shortDescription" : "",
97
+ "shape" : "[1]",
98
+ "name" : "input_ids",
99
+ "type" : "MultiArray"
100
+ },
101
+ {
102
+ "hasShapeFlexibility" : "0",
103
+ "isOptional" : "0",
104
+ "dataType" : "Int32",
105
+ "formattedType" : "MultiArray (Int32 1)",
106
+ "shortDescription" : "",
107
+ "shape" : "[1]",
108
+ "name" : "cache_length",
109
+ "type" : "MultiArray"
110
+ },
111
+ {
112
+ "hasShapeFlexibility" : "0",
113
+ "isOptional" : "0",
114
+ "dataType" : "Float16",
115
+ "formattedType" : "MultiArray (Float16 1 × 1536 × 1 × 224)",
116
+ "shortDescription" : "",
117
+ "shape" : "[1, 1536, 1, 224]",
118
+ "name" : "key_cache",
119
+ "type" : "MultiArray"
120
+ },
121
+ {
122
+ "hasShapeFlexibility" : "0",
123
+ "isOptional" : "0",
124
+ "dataType" : "Float16",
125
+ "formattedType" : "MultiArray (Float16 1 × 1536 × 1 × 224)",
126
+ "shortDescription" : "",
127
+ "shape" : "[1, 1536, 1, 224]",
128
+ "name" : "value_cache",
129
+ "type" : "MultiArray"
130
+ },
131
+ {
132
+ "hasShapeFlexibility" : "0",
133
+ "isOptional" : "0",
134
+ "dataType" : "Float16",
135
+ "formattedType" : "MultiArray (Float16 1 × 224)",
136
+ "shortDescription" : "",
137
+ "shape" : "[1, 224]",
138
+ "name" : "kv_cache_update_mask",
139
+ "type" : "MultiArray"
140
+ },
141
+ {
142
+ "hasShapeFlexibility" : "0",
143
+ "isOptional" : "0",
144
+ "dataType" : "Float16",
145
+ "formattedType" : "MultiArray (Float16 1 × 384 × 1 × 1500)",
146
+ "shortDescription" : "",
147
+ "shape" : "[1, 384, 1, 1500]",
148
+ "name" : "encoder_output_embeds",
149
+ "type" : "MultiArray"
150
+ },
151
+ {
152
+ "hasShapeFlexibility" : "0",
153
+ "isOptional" : "0",
154
+ "dataType" : "Float16",
155
+ "formattedType" : "MultiArray (Float16 1 × 224)",
156
+ "shortDescription" : "",
157
+ "shape" : "[1, 224]",
158
+ "name" : "decoder_key_padding_mask",
159
+ "type" : "MultiArray"
160
+ }
161
+ ],
162
+ "generatedClassName" : "TextDecoder",
163
+ "method" : "predict"
164
+ }
165
+ ]
openai_whisper-tiny.en/TextDecoder.mlmodelc/model.mil ADDED
The diff for this file is too large to render. See raw diff
 
openai_whisper-tiny.en/TextDecoder.mlmodelc/weights/weight.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3e647a216be345d47805bcd85dfae64840f154cfbb4c4f1d1b07da6a2dd8c72c
3
+ size 59215664
openai_whisper-tiny.en/config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"_name_or_path": "openai/whisper-tiny.en", "activation_dropout": 0.0, "activation_function": "gelu", "architectures": ["WhisperForConditionalGeneration"], "attention_dropout": 0.0, "begin_suppress_tokens": [220, 50256], "bos_token_id": 50257, "d_model": 384, "decoder_attention_heads": 6, "decoder_ffn_dim": 1536, "decoder_layerdrop": 0.0, "decoder_layers": 4, "decoder_start_token_id": 50257, "dropout": 0.0, "encoder_attention_heads": 6, "encoder_ffn_dim": 1536, "encoder_layerdrop": 0.0, "encoder_layers": 4, "eos_token_id": 50256, "forced_decoder_ids": [[1, 50362]], "init_std": 0.02, "is_encoder_decoder": true, "max_length": 448, "max_source_positions": 1500, "max_target_positions": 448, "model_type": "whisper", "num_hidden_layers": 4, "num_mel_bins": 80, "pad_token_id": 50256, "scale_embedding": false, "suppress_tokens": [1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90, 91, 92, 93, 357, 366, 438, 532, 685, 705, 796, 930, 1058, 1220, 1267, 1279, 1303, 1343, 1377, 1391, 1635, 1782, 1875, 2162, 2361, 2488, 3467, 4008, 4211, 4600, 4808, 5299, 5855, 6329, 7203, 9609, 9959, 10563, 10786, 11420, 11709, 11907, 13163, 13697, 13700, 14808, 15306, 16410, 16791, 17992, 19203, 19510, 20724, 22305, 22935, 27007, 30109, 30420, 33409, 34949, 40283, 40493, 40549, 47282, 49146, 50257, 50357, 50358, 50359, 50360, 50361], "torch_dtype": "float32", "transformers_version": "4.27.0.dev0", "use_cache": true, "vocab_size": 51864}
openai_whisper-tiny.en/generation_config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"alignment_heads": [[1, 0], [2, 0], [2, 5], [3, 0], [3, 1], [3, 2], [3, 3], [3, 4]], "begin_suppress_tokens": [220, 50256], "bos_token_id": 50257, "decoder_start_token_id": 50257, "eos_token_id": 50256, "forced_decoder_ids": [[1, 50362]], "is_multilingual": false, "max_initial_timestamp_index": 50, "max_length": 448, "no_timestamps_token_id": 50362, "pad_token_id": 50256, "prev_sot_token_id": 50360, "return_timestamps": false, "suppress_tokens": [1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90, 91, 92, 93, 357, 366, 438, 532, 685, 705, 796, 930, 1058, 1220, 1267, 1279, 1303, 1343, 1377, 1391, 1635, 1782, 1875, 2162, 2361, 2488, 3467, 4008, 4211, 4600, 4808, 5299, 5855, 6329, 7203, 9609, 9959, 10563, 10786, 11420, 11709, 11907, 13163, 13697, 13700, 14808, 15306, 16410, 16791, 17992, 19203, 19510, 20724, 22305, 22935, 27007, 30109, 30420, 33409, 34949, 40283, 40493, 40549, 47282, 49146, 50257, 50357, 50358, 50359, 50360, 50361], "transformers_version": "4.31.0.dev0"}