Model.swift
1.8 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
import Foundation
func getResource(_ forResource: String, _ ofType: String) -> String {
let path = Bundle.main.path(forResource: forResource, ofType: ofType)
precondition(
path != nil,
"\(forResource).\(ofType) does not exist!\n" + "Remember to change \n"
+ " Build Phases -> Copy Bundle Resources\n" + "to add it!"
)
return path!
}
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
/// to download pre-trained models
/// sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20 (Bilingual, Chinese + English)
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/zipformer-transducer-models.html
func getBilingualStreamZhEnZipformer20230220() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder-epoch-99-avg-1", "onnx")
let decoder = getResource("decoder-epoch-99-avg-1", "onnx")
let joiner = getResource("joiner-epoch-99-avg-1", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
transducer: sherpaOnnxOnlineTransducerModelConfig(
encoder: encoder,
decoder: decoder,
joiner: joiner),
numThreads: 2,
modelType: "zipformer"
)
}
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/index.html
func getBilingualStreamingZhEnParaformer() -> SherpaOnnxOnlineModelConfig {
let encoder = getResource("encoder.int8", "onnx")
let decoder = getResource("decoder.int8", "onnx")
let tokens = getResource("tokens", "txt")
return sherpaOnnxOnlineModelConfig(
tokens: tokens,
paraformer: sherpaOnnxOnlineParaformerModelConfig(
encoder: encoder,
decoder: decoder),
numThreads: 1,
modelType: "paraformer"
)
}
/// Please refer to
/// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
/// to add more models if you need