File size: 7,155 Bytes
44d964a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8670926
 
 
 
 
 
 
 
44d964a
 
 
 
1acaa19
 
 
44d964a
 
 
 
 
 
 
d20404a
 
1acaa19
 
 
 
 
295de00
198df44
 
295de00
 
44d964a
 
 
 
 
 
 
 
 
 
 
 
1acaa19
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8031785
 
1acaa19
 
 
 
 
 
 
 
 
33ee1bb
1acaa19
 
 
 
 
 
 
 
 
 
33ee1bb
e694402
1acaa19
 
 
 
 
 
 
f55c594
 
 
 
 
 
 
 
 
 
a1da02d
 
 
 
 
 
 
 
 
 
3cd7d59
 
 
44d964a
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
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
{
    "models": [
        // Configuration for the built-in models. You can remove any of these 
        // if you don't want to use the default models.
        {
            "name": "tiny",
            "url": "tiny" 
        },
        {
            "name": "base",
            "url": "base"
        },
        {
            "name": "small",
            "url": "small"
        },
        {
            "name": "medium",
            "url": "medium"
        },
        {
            "name": "large",
            "url": "large"
        },
        {
            "name": "large-v2",
            "url": "large-v2"
        },
        // Uncomment to add custom Japanese models
        //{
        //    "name": "whisper-large-v2-mix-jp",
        //    "url": "vumichien/whisper-large-v2-mix-jp",
        //    // The type of the model. Can be "huggingface" or "whisper" - "whisper" is the default.
        //    // HuggingFace models are loaded using the HuggingFace transformers library and then converted to Whisper models.
        //    "type": "huggingface",
        //},
        //{
        //    "name": "local-model",
        //    "url": "path/to/local/model",
        //},
        //{
        //    "name": "remote-model",
        //    "url": "https://example.com/path/to/model",
        //}
    ],
    // Configuration options that will be used if they are not specified in the command line arguments.

    // * WEBUI options *

    // Maximum audio file length in seconds, or -1 for no limit. Ignored by CLI.
    "input_audio_max_duration": 600,
    // True to share the app on HuggingFace.
    "share": false,
    // The host or IP to bind to. If None, bind to localhost.
    "server_name": null,
    // The port to bind to.
    "server_port": 7860,
    // The number of workers to use for the web server. Use -1 to disable queueing.
    "queue_concurrency_count": 1,
    // Whether or not to automatically delete all uploaded files, to save disk space
    "delete_uploaded_files": true,

    // * General options *

    // The default implementation to use for Whisper. Can be "whisper" or "faster-whisper".
    // Note that you must either install the requirements for faster-whisper (requirements-fasterWhisper.txt) 
    // or whisper (requirements.txt)
    "whisper_implementation": "whisper",

    // The default model name.
    "default_model_name": "medium",
    // The default VAD.
    "default_vad": "silero-vad",
    // A commma delimited list of CUDA devices to use for parallel processing. If None, disable parallel processing.
    "vad_parallel_devices": "",
    // The number of CPU cores to use for VAD pre-processing.
    "vad_cpu_cores": 1,
    // The number of seconds before inactivate processes are terminated. Use 0 to close processes immediately, or None for no timeout.
    "vad_process_timeout": 1800,
    // True to use all available GPUs and CPU cores for processing. Use vad_cpu_cores/vad_parallel_devices to specify the number of CPU cores/GPUs to use.
    "auto_parallel": false,
    // Directory to save the outputs (CLI will use the current directory if not specified)
    "output_dir": null,
    // The path to save model files; uses ~/.cache/whisper by default
    "model_dir": null,
    // Device to use for PyTorch inference, or Null to use the default device
    "device": null,
    // Whether to print out the progress and debug messages
    "verbose": true,
    // Whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate')
    "task": "transcribe",
    // Language spoken in the audio, specify None to perform language detection
    "language": null,
    // The window size (in seconds) to merge voice segments
    "vad_merge_window": 5,
    // The maximum size (in seconds) of a voice segment
    "vad_max_merge_size": 30,
    // The padding (in seconds) to add to each voice segment
    "vad_padding": 1,
    // Whether or not to prepend the initial prompt to each VAD segment (prepend_all_segments), or just the first segment (prepend_first_segment)
    "vad_initial_prompt_mode": "prepend_first_segment",
    // The window size of the prompt to pass to Whisper
    "vad_prompt_window": 3,
    // Temperature to use for sampling
    "temperature": 0,
    // Number of candidates when sampling with non-zero temperature
    "best_of": 5,
    // Number of beams in beam search, only applicable when temperature is zero
    "beam_size": 5,
    // Optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search
    "patience": 1,
    // Optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple length normalization by default
    "length_penalty": null,
    // Comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations
    "suppress_tokens": "-1",
    // Optional text to provide as a prompt for the first window
    "initial_prompt": null,
    // If True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop
    "condition_on_previous_text": true,
    // Whether to perform inference in fp16; True by default
    "fp16": true,
    // The compute type used by faster-whisper. Can be "int8". "int16" or "float16".
    "compute_type": "auto",
    // Temperature to increase when falling back when the decoding fails to meet either of the thresholds below
    "temperature_increment_on_fallback": 0.2,
    // If the gzip compression ratio is higher than this value, treat the decoding as failed
    "compression_ratio_threshold": 2.4,
    // If the average log probability is lower than this value, treat the decoding as failed
    "logprob_threshold": -1.0,
    // If the probability of the <no-speech> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence
    "no_speech_threshold": 0.6,

    // (experimental) extract word-level timestamps and refine the results based on them
    "word_timestamps": false, 
    // if word_timestamps is True, merge these punctuation symbols with the next word
    "prepend_punctuations": "\"\'“¿([{-",
    // if word_timestamps is True, merge these punctuation symbols with the previous word
    "append_punctuations": "\"\'.。,,!!??::”)]}、",
    // (requires --word_timestamps True) underline each word as it is spoken in srt and vtt
    "highlight_words": false,

    // Diarization settings
    "auth_token": null,
    // Whether to perform speaker diarization
    "diarization": false,
    // The number of speakers to detect
    "diarization_speakers": 2,
    // The minimum number of speakers to detect
    "diarization_min_speakers": 1,
    // The maximum number of speakers to detect
    "diarization_max_speakers": 8,
    // The number of seconds before inactivate processes are terminated. Use 0 to close processes immediately, or None for no timeout.
    "diarization_process_timeout": 60,
}