Add text decoder models (embedding + decoder) for full CoreML pipeline
Browse files- config.json +16 -32
- decoder.mlmodelc/analytics/coremldata.bin +3 -0
- decoder.mlmodelc/coremldata.bin +3 -0
- decoder.mlmodelc/metadata.json +606 -0
- decoder.mlmodelc/model.mil +0 -0
- decoder.mlmodelc/weights/weight.bin +3 -0
- embedding.mlmodelc/analytics/coremldata.bin +3 -0
- embedding.mlmodelc/coremldata.bin +3 -0
- embedding.mlmodelc/metadata.json +65 -0
- embedding.mlmodelc/model.mil +21 -0
- embedding.mlmodelc/weights/weight.bin +3 -0
config.json
CHANGED
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@@ -1,35 +1,19 @@
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{
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-
"model_type": "qwen3-asr-
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"source_model": "Qwen/Qwen3-ASR-0.6B",
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1000,
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1500,
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2000,
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3000
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],
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"variants": {
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"int8": {
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"file": "encoder_int8.mlpackage",
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"quantization": "int8_palettize"
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},
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"int4": {
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"file": "encoder_int4.mlpackage",
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"quantization": "int4_palettize"
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}
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},
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-
"default_variant": "int8"
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}
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{
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+
"model_type": "qwen3-asr-decoder-coreml",
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"source_model": "Qwen/Qwen3-ASR-0.6B",
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+
"max_seq_length": 1024,
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+
"hidden_size": 1024,
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+
"num_layers": 28,
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+
"num_heads": 16,
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"num_kv_heads": 8,
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"head_dim": 128,
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+
"intermediate_size": 3072,
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+
"vocab_size": 151936,
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+
"rms_norm_eps": 1e-06,
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+
"rope_theta": 1000000.0,
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"quantization": "int8_palettize",
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"files": {
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+
"embedding": "embedding.mlpackage",
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"decoder": "decoder.mlpackage"
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+
}
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}
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decoder.mlmodelc/analytics/coremldata.bin
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:a79916489c7f48e36f27bba2b338a78f5dcb33136a24523b42cfb7d9bb80643e
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+
size 243
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decoder.mlmodelc/coremldata.bin
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:ef85d0192c459be0254385c22fd7d67fad251cf7ff1654128482b312916d57c0
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+
size 2209
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decoder.mlmodelc/metadata.json
ADDED
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@@ -0,0 +1,606 @@
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| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"metadataOutputVersion" : "3.0",
|
| 4 |
+
"storagePrecision" : "Mixed (Float16, Palettized (8 bits), UInt8)",
|
| 5 |
+
"outputSchema" : [
|
| 6 |
+
{
|
| 7 |
+
"hasShapeFlexibility" : "0",
|
| 8 |
+
"isOptional" : "0",
|
| 9 |
+
"dataType" : "Float16",
|
| 10 |
+
"formattedType" : "MultiArray (Float16 1 × 1 × 151936)",
|
| 11 |
+
"shortDescription" : "",
|
| 12 |
+
"shape" : "[1, 1, 151936]",
|
| 13 |
+
"name" : "logits",
|
| 14 |
+
"type" : "MultiArray"
|
| 15 |
+
}
|
| 16 |
+
],
|
| 17 |
+
"modelParameters" : [
|
| 18 |
+
|
| 19 |
+
],
|
| 20 |
+
"specificationVersion" : 9,
|
| 21 |
+
"mlProgramOperationTypeHistogram" : {
|
| 22 |
+
"Ios18.expandDims" : 56,
|
| 23 |
+
"Ios18.mul" : 619,
|
| 24 |
+
"Ios18.cos" : 1,
|
| 25 |
+
"Ios18.softmax" : 28,
|
| 26 |
+
"Ios18.rsqrt" : 113,
|
| 27 |
+
"Ios18.matmul" : 56,
|
| 28 |
+
"Ios16.reduceMean" : 113,
|
| 29 |
+
"Ios18.sin" : 1,
|
| 30 |
+
"Ios18.readState" : 168,
|
| 31 |
+
"Tile" : 56,
|
| 32 |
+
"Ios18.add" : 309,
|
| 33 |
+
"Ios18.writeState" : 112,
|
| 34 |
+
"Ios18.reshape" : 171,
|
| 35 |
+
"Ios18.constexprLutToDense" : 197,
|
| 36 |
+
"Ios18.linear" : 197,
|
| 37 |
+
"Ios18.concat" : 56,
|
| 38 |
+
"Ios18.transpose" : 112,
|
| 39 |
+
"OneHot" : 1,
|
| 40 |
+
"Ios18.sub" : 57,
|
| 41 |
+
"Ios18.pow" : 113,
|
| 42 |
+
"Ios18.cast" : 4,
|
| 43 |
+
"Ios18.silu" : 28,
|
| 44 |
+
"Ios18.sliceByIndex" : 112
|
| 45 |
+
},
|
| 46 |
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decoder.mlmodelc/model.mil
ADDED
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The diff for this file is too large to render.
See raw diff
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decoder.mlmodelc/weights/weight.bin
ADDED
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embedding.mlmodelc/analytics/coremldata.bin
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embedding.mlmodelc/metadata.json
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|
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],
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|
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|
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|
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|
| 58 |
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|
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|
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|
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],
|
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|
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|
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|
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|
embedding.mlmodelc/model.mil
ADDED
|
@@ -0,0 +1,21 @@
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
program(1.3)
|
| 2 |
+
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3510.2.1"}, {"coremlc-version", "3500.32.1"}})]
|
| 3 |
+
{
|
| 4 |
+
func main<ios18>(tensor<int32, [1, 1]> token_id) {
|
| 5 |
+
int32 var_6_batch_dims_0 = const()[name = string("op_6_batch_dims_0"), val = int32(0)];
|
| 6 |
+
bool var_6_validate_indices_0 = const()[name = string("op_6_validate_indices_0"), val = bool(false)];
|
| 7 |
+
tensor<fp16, [151936, 1024]> embedding_weight_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor<uint8, [151936, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64))), lut = tensor<fp16, [1, 1, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(155582592))))[name = string("embedding_weight_to_fp16_palettized")];
|
| 8 |
+
int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
|
| 9 |
+
tensor<bool, [1, 1]> greater_equal_0 = greater_equal(x = token_id, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
|
| 10 |
+
int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(151936)];
|
| 11 |
+
tensor<int32, [1, 1]> add_0 = add(x = token_id, y = slice_by_index_0)[name = string("add_0")];
|
| 12 |
+
tensor<int32, [1, 1]> select_0 = select(a = token_id, b = add_0, cond = greater_equal_0)[name = string("select_0")];
|
| 13 |
+
int32 greater_equal_0_y_0_1 = const()[name = string("greater_equal_0_y_0_1"), val = int32(0)];
|
| 14 |
+
tensor<bool, [1, 1]> greater_equal_0_1 = greater_equal(x = select_0, y = greater_equal_0_y_0_1)[name = string("greater_equal_0_1")];
|
| 15 |
+
int32 slice_by_index_0_1 = const()[name = string("slice_by_index_0_1"), val = int32(151936)];
|
| 16 |
+
tensor<int32, [1, 1]> add_0_1 = add(x = select_0, y = slice_by_index_0_1)[name = string("add_0_1")];
|
| 17 |
+
tensor<int32, [1, 1]> select_0_1 = select(a = select_0, b = add_0_1, cond = greater_equal_0_1)[name = string("select_0_1")];
|
| 18 |
+
int32 op_6_cast_fp16_axis_0 = const()[name = string("op_6_cast_fp16_axis_0"), val = int32(0)];
|
| 19 |
+
tensor<fp16, [1, 1, 1024]> embedding = gather(axis = op_6_cast_fp16_axis_0, batch_dims = var_6_batch_dims_0, indices = select_0_1, validate_indices = var_6_validate_indices_0, x = embedding_weight_to_fp16_palettized)[name = string("op_6_cast_fp16")];
|
| 20 |
+
} -> (embedding);
|
| 21 |
+
}
|
embedding.mlmodelc/weights/weight.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:e3c98211cd573376f8a2f3a41bab50581fb66d9657e407938db52d288f7df5e7
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| 3 |
+
size 155583168
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