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SaT.mlmodelc/analytics/coremldata.bin
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oid sha256:
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size 241
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version https://git-lfs.github.com/spec/v1
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oid sha256:b8d1e677e15bf5d02cad0b2941ce5b932e8ef4cf5f96cfa4d644f5a7fe02c4eb
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size 241
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SaT.mlmodelc/coremldata.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 347
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version https://git-lfs.github.com/spec/v1
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oid sha256:2bcd0b3ee1481feafa7931ba0eb87d25bff4c4370ed2fbe74c8a44b3e05dc505
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size 347
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SaT.mlmodelc/metadata.json
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@@ -52,9 +52,9 @@
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"name" : "MLModelType_mlProgram"
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},
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"userDefinedMetadata" : {
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"com.github.apple.coremltools.source_dialect" : "TorchScript",
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"com.github.apple.coremltools.source" : "torch==2.9.0"
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"com.github.apple.coremltools.version" : "8.3.0"
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},
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"inputSchema" : [
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{
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"name" : "MLModelType_mlProgram"
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},
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"userDefinedMetadata" : {
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"com.github.apple.coremltools.version" : "8.3.0",
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"com.github.apple.coremltools.source_dialect" : "TorchScript",
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"com.github.apple.coremltools.source" : "torch==2.9.0"
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},
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"inputSchema" : [
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{
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SaT.mlmodelc/model.mil
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program(1.3)
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[buildInfo = dict<string, string>({{"coremlc-component-MIL", "
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{
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func main<ios18>(tensor<int32, [1, 512]> attention_mask, tensor<int32, [1, 512]> input_ids) {
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tensor<fp32, [250002, 768]> base_model_roberta_embeddings_word_embeddings_weight_quantized = constexpr_blockwise_shift_scale(data = tensor<int8, [250002, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64))), scale = tensor<fp32, [250002, 24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192001664))))[name = string("base_model_roberta_embeddings_word_embeddings_weight_quantized")];
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program(1.3)
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[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3510.2.1"}, {"coremlc-version", "3500.32.1"}})]
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{
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func main<ios18>(tensor<int32, [1, 512]> attention_mask, tensor<int32, [1, 512]> input_ids) {
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tensor<fp32, [250002, 768]> base_model_roberta_embeddings_word_embeddings_weight_quantized = constexpr_blockwise_shift_scale(data = tensor<int8, [250002, 768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64))), scale = tensor<fp32, [250002, 24]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192001664))))[name = string("base_model_roberta_embeddings_word_embeddings_weight_quantized")];
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SaT.mlpackage/Data/com.apple.CoreML/SaT.mlmodel
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version https://git-lfs.github.com/spec/v1
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oid sha256:5c5c55c303db68eee3e88b500dbfa1707a69b917b63cb9d9cb843b7c748f5151
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size 36026
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SaT.mlpackage/Data/com.apple.CoreML/weights/weight.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:08b5d724996325ea649fad4b140360e29a08a1eb6ecdb4329455a55bd6973c59
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size 240860864
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SaT.mlpackage/Manifest.json
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{
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"fileFormatVersion": "1.0.0",
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"itemInfoEntries": {
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"13AE9F45-9157-4F69-9E54-66DF8821F0F6": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Weights",
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"name": "weights",
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"path": "com.apple.CoreML/weights"
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},
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"419EF5EF-7790-4402-A426-FD90BD52869F": {
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"author": "com.apple.CoreML",
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"description": "CoreML Model Specification",
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"name": "SaT.mlmodel",
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"path": "com.apple.CoreML/SaT.mlmodel"
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}
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},
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"rootModelIdentifier": "419EF5EF-7790-4402-A426-FD90BD52869F"
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}
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