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{
"models": {
"whisper": [
// 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-v1",
"url": "large-v1"
},
{
"name": "large-v2",
"url": "large-v2"
},
{
"name": "large-v3",
"url": "large-v3"
},
{
"name": "large-v3-turbo",
"url": "large-v3-turbo"
}
// 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",
//}
],
"m2m100": [
{
"name": "m2m100_1.2B-ct2fast/michaelfeil",
"url": "michaelfeil/ct2fast-m2m100_1.2B",
"type": "huggingface",
"tokenizer_url": "facebook/m2m100_1.2B"
},
{
"name": "m2m100_1.2B/facebook",
"url": "facebook/m2m100_1.2B",
"type": "huggingface"
},
{
"name": "m2m100_418M-ct2fast/michaelfeil",
"url": "michaelfeil/ct2fast-m2m100_418M",
"type": "huggingface",
"tokenizer_url": "facebook/m2m100_418M"
},
{
"name": "m2m100_418M/facebook",
"url": "facebook/m2m100_418M",
"type": "huggingface"
},
{
"name": "m2m100-12B-last-ckpt/facebook",
"url": "facebook/m2m100-12B-last-ckpt",
"type": "huggingface"
},
{
"name": "m2m100-12B-ct2fast/michaelfeil",
"url": "michaelfeil/ct2fast-m2m100-12B-last-ckpt",
"type": "huggingface",
"tokenizer_url": "facebook/m2m100-12B-last-ckpt"
}
],
"nllb": [
{
"name": "nllb-200-distilled-1.3B-ct2:int8/JustFrederik",
"url": "JustFrederik/nllb-200-distilled-1.3B-ct2-int8",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-1.3B"
},
{
"name": "nllb-200-distilled-1.3B-ct2fast:int8_float16/michaelfeil",
"url": "michaelfeil/ct2fast-nllb-200-distilled-1.3B",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-1.3B"
},
{
"name": "nllb-200-distilled-1.3B-ct2:float16/JustFrederik",
"url": "JustFrederik/nllb-200-distilled-1.3B-ct2-float16",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-1.3B"
},
{
"name": "nllb-200-distilled-1.3B-ct2/JustFrederik",
"url": "JustFrederik/nllb-200-distilled-1.3B-ct2",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-1.3B"
},
{
"name": "nllb-200-1.3B-ct2:int8/JustFrederik",
"url": "JustFrederik/nllb-200-1.3B-ct2-int8",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-1.3B"
},
{
"name": "nllb-200-1.3B-ct2:float16/JustFrederik",
"url": "JustFrederik/nllb-200-1.3B-ct2-float16",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-1.3B"
},
{
"name": "nllb-200-1.3B-ct2/JustFrederik",
"url": "JustFrederik/nllb-200-1.3B-ct2",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-1.3B"
},
{
"name": "nllb-200-distilled-1.3B/facebook",
"url": "facebook/nllb-200-distilled-1.3B",
"type": "huggingface"
},
{
"name": "nllb-200-1.3B/facebook",
"url": "facebook/nllb-200-1.3B",
"type": "huggingface"
},
{
"name": "nllb-200-3.3B-ct2fast:int8_float16/michaelfeil",
"url": "michaelfeil/ct2fast-nllb-200-3.3B",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-3.3B"
},
{
"name": "nllb-200-3.3B-ct2:float16/JustFrederik",
"url": "JustFrederik/nllb-200-3.3B-ct2-float16",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-3.3B"
},
{
"name": "nllb-200-3.3B/facebook",
"url": "facebook/nllb-200-3.3B",
"type": "huggingface"
},
{
"name": "nllb-200-distilled-600M/facebook",
"url": "facebook/nllb-200-distilled-600M",
"type": "huggingface"
},
{
"name": "nllb-200-distilled-600M-ct2:int8/JustFrederik",
"url": "JustFrederik/nllb-200-distilled-600M-ct2-int8",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-600M"
},
{
"name": "nllb-200-distilled-600M-ct2:float16/JustFrederik",
"url": "JustFrederik/nllb-200-distilled-600M-ct2-float16",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-600M"
},
{
"name": "nllb-200-distilled-600M-ct2/JustFrederik",
"url": "JustFrederik/nllb-200-distilled-600M-ct2",
"type": "huggingface",
"tokenizer_url": "facebook/nllb-200-distilled-600M"
}
],
"mt5": [
{
"name": "mt5-zh-ja-en-trimmed/K024",
"url": "K024/mt5-zh-ja-en-trimmed",
"type": "huggingface"
},
{
"name": "mt5-zh-ja-en-trimmed-fine-tuned-v1/engmatic-earth",
"url": "engmatic-earth/mt5-zh-ja-en-trimmed-fine-tuned-v1",
"type": "huggingface"
}
],
"ALMA": [
{
"name": "ALMA-7B-GPTQ/TheBloke",
"url": "TheBloke/ALMA-7B-GPTQ",
"type": "huggingface"
},
{
"name": "ALMA-13B-GPTQ/TheBloke",
"url": "TheBloke/ALMA-13B-GPTQ",
"type": "huggingface"
},
{
"name": "ALMA-7B-GGUF-Q4_K_M/TheBloke",
"url": "TheBloke/ALMA-7B-GGUF",
"type": "huggingface",
"model_file": "alma-7b.Q4_K_M.gguf",
"tokenizer_url": "haoranxu/ALMA-7B"
},
{
"name": "ALMA-13B-GGUF-Q4_K_M/TheBloke",
"url": "TheBloke/ALMA-13B-GGUF",
"type": "huggingface",
"model_file": "alma-13b.Q4_K_M.gguf",
"tokenizer_url": "haoranxu/ALMA-13B"
},
{
"name": "ALMA-7B-ct2:int8_float16/avan",
"url": "avans06/ALMA-7B-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "haoranxu/ALMA-7B"
},
{
"name": "ALMA-13B-ct2:int8_float16/avan",
"url": "avans06/ALMA-13B-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "haoranxu/ALMA-13B"
},
{
"name": "ALMA-7B/haoranxu",
"url": "haoranxu/ALMA-7B",
"type": "huggingface"
},
{
"name": "ALMA-13B/haoranxu",
"url": "haoranxu/ALMA-13B",
"type": "huggingface"
}
],
"madlad400": [
{
"name": "madlad400-3b-mt-ct2-int8_float16/SoybeanMilk",
"url": "SoybeanMilk/madlad400-3b-mt-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "jbochi/madlad400-3b-mt"
},
{
"name": "madlad400-7b-mt-bt-ct2-int8_float16/avan",
"url": "avans06/madlad400-7b-mt-bt-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "jbochi/madlad400-7b-mt-bt"
},
{
"name": "madlad400-10b-mt-ct2-int8_float16/SoybeanMilk",
"url": "SoybeanMilk/madlad400-10b-mt-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "jbochi/madlad400-10b-mt"
},
{
"name": "madlad400-3b-mt/jbochi",
"url": "jbochi/madlad400-3b-mt",
"type": "huggingface"
},
{
"name": "madlad400-7b-mt-bt/jbochi",
"url": "jbochi/madlad400-7b-mt-bt",
"type": "huggingface"
},
{
"name": "madlad400-10b-mt/jbochi",
"url": "jbochi/madlad400-10b-mt",
"type": "huggingface"
}
],
"seamless": [
//{
// "name": "hf-seamless-m4t-medium/facebook",
// "url": "facebook/hf-seamless-m4t-medium",
// "type": "huggingface"
//},
//{
// "name": "seamless-m4t-large/facebook",
// "url": "facebook/seamless-m4t-large",
// "type": "huggingface"
//},
{
"name": "seamless-m4t-v2-large/facebook",
"url": "facebook/seamless-m4t-v2-large",
"type": "huggingface"
}
],
"Llama": [
{
"name": "Meta-Llama-3.2-8B-Instruct-ct2-int8_float16/avan",
"url": "avans06/Meta-Llama-3.2-8B-Instruct-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "avans06/Meta-Llama-3.2-8B-Instruct-ct2-int8_float16"
},
{
"name": "Meta-Llama-3.1-8B-Instruct-ct2-int8_float16/avan",
"url": "avans06/Meta-Llama-3.1-8B-Instruct-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "avans06/Meta-Llama-3.1-8B-Instruct-ct2-int8_float16"
},
{
"name": "Meta-Llama-3-8B-Instruct-ct2-int8_float16/avan",
"url": "avans06/Meta-Llama-3-8B-Instruct-ct2-int8_float16",
"type": "huggingface",
"tokenizer_url": "avans06/Meta-Llama-3-8B-Instruct-ct2-int8_float16"
},
{
"name": "Meta-Llama-3.2-3B-Instruct-ct2-int8/jncraton",
"url": "jncraton/Llama-3.2-3B-Instruct-ct2-int8",
"type": "huggingface",
"tokenizer_url": "jncraton/Llama-3.2-3B-Instruct-ct2-int8"
}
]
},
// 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": 1800,
// 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": "faster-whisper",
// The default model name.
"default_model_name": "large-v2",
// 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": 90,
// 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,
// [faster-whisper] The parameter for repetition penalty. Between 1.0 and infinity. 1.0 means no penalty. Default to 1.0.
"repetition_penalty": 1.0,
// [faster-whisper] The model ensures that a sequence of words of no_repeat_ngram_size isn’t repeated in the output sequence. If specified, it must be a positive integer greater than 1.
"no_repeat_ngram_size": 0,
// (experimental) extract word-level timestamps and refine the results based on them
"word_timestamps": true,
// 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,
// Whisper Segments Filter
"whisper_segments_filter": false,
"whisper_segments_filters": [
"avg_logprob < -0.9",
"(durationLen < 1.5 || segment_last), textLen > 5, avg_logprob < -0.4, no_speech_prob > 0.5",
"(durationLen < 1.5 || segment_last), textLen > 5, avg_logprob < -0.4, no_speech_prob > 0.07, compression_ratio < 0.9",
"(durationLen < 1.5 || segment_last), compression_ratio < 0.9, no_speech_prob > 0.1"
],
// Translation - The maximum batch size.
"translation_batch_size": 2,
// Translation - Prevent repetitions of ngrams with this size (set 0 to disable).
"translation_no_repeat_ngram_size": 4,
// Translation - Beam size (1 for greedy search).
"translation_num_beams": 3,
// Translation - Torch Dtype float16, Load the float32 translation model with float16 when the system supports GPU (reducing VRAM usage, not applicable to quantized models, such as Ctranslate2, GPTQ, GGUF).
"translation_torch_dtype_float16": true,
// Translation - Using Bitsandbytes, Load the float32 translation model into mixed-8bit or 4bit precision quantized model(not applicable to quantized models, such as Ctranslate2, GPTQ, GGUF).
"translation_using_bitsandbytes": null
} |