Faster Whisper is designed to process audio files using various Whisper models, with options for transcription formatting, language translation and more.

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Models

• tiny
• base
• small
• medium
• large-v1
• large-v2
• large-v3
• distil-large-v2
• distil-large-v3
• turbo

Input

Input	Type	Description
audio	Path	URL to Audio file
audio_base64	str	Base64-encoded audio file
model	str	Choose a Whisper model. Choices: "tiny", "base", "small", "medium", "large-v1", "large-v2", "large-v3", "distil-large-v2", "distil-large-v3", "turbo". Default: "base"
transcription	str	Choose the format for the transcription. Choices: "plain_text", "formatted_text", "srt", "vtt". Default: "plain_text"
translate	bool	Translate the text to English when set to True. Default: False
translation	str	Choose the format for the translation. Choices: "plain_text", "formatted_text", "srt", "vtt". Default: "plain_text"
language	str	Language spoken in the audio, specify None to perform language detection. Default: None
temperature	float	Temperature to use for sampling. Default: 0
best_of	int	Number of candidates when sampling with non-zero temperature. Default: 5
beam_size	int	Number of beams in beam search, only applicable when temperature is zero. Default: 5
patience	float	Optional patience value to use in beam decoding. Default: None
length_penalty	float	Optional token length penalty coefficient (alpha). Default: None
suppress_tokens	str	Comma-separated list of token ids to suppress during sampling. Default: "-1"
initial_prompt	str	Optional text to provide as a prompt for the first window. Default: None
condition_on_previous_text	bool	If True, provide the previous output of the model as a prompt for the next window. Default: True
temperature_increment_on_fallback	float	Temperature to increase when falling back when the decoding fails. Default: 0.2
compression_ratio_threshold	float	If the gzip compression ratio is higher than this value, treat the decoding as failed. Default: 2.4
logprob_threshold	float	If the average log probability is lower than this value, treat the decoding as failed. Default: -1.0
no_speech_threshold	float	If the probability of the token is higher than this value, consider the segment as silence. Default: 0.6
enable_vad	bool	If True, use the voice activity detection (VAD) to filter out parts of the audio without speech. This step is using the Silero VAD model. Default: False
word_timestamps	bool	If True, include word timestamps in the output. Default: False

Example

The following inputs can be used for testing the model:

{
  "input": {
    "audio": "https://github.com./runpod-workers/sample-inputs/raw/main/audio/gettysburg.wav",
    "model": "turbo"
  }
}

producing an output like this:

{
  "segments": [
    {
      "id": 1,
      "seek": 106,
      "start": 0.11,
      "end": 3.11,
      "text": " Hello and welcome!",
      "tokens": [50364, 25, 7, 287, 50514],
      "temperature": 0.1,
      "avg_logprob": -0.8348079785480325,
      "compression_ratio": 0.5789473684210527,
      "no_speech_prob": 0.1453857421875
    }
  ],
  "detected_language": "en",
  "transcription": "Hello and welcome!",
  "translation": null,
  "device": "cuda",
  "model": "turbo",
  "translation_time": 0.3796223163604736
}