https://github.com/runpod-workers/worker-faster_whisper
faster-whisper as serverless endpoint
https://github.com/runpod-workers/worker-faster_whisper
ai docker faster-whsiper runpod whisper
Last synced: 3 months ago
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faster-whisper as serverless endpoint
- Host: GitHub
- URL: https://github.com/runpod-workers/worker-faster_whisper
- Owner: runpod-workers
- License: mit
- Created: 2023-05-30T16:17:36.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2025-11-21T06:33:09.000Z (7 months ago)
- Last Synced: 2025-11-21T08:30:20.344Z (7 months ago)
- Topics: ai, docker, faster-whsiper, runpod, whisper
- Language: Python
- Homepage: https://runpod.io
- Size: 1.98 MB
- Stars: 125
- Watchers: 4
- Forks: 109
- Open Issues: 18
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
[Faster Whisper](https://github.com/guillaumekln/faster-whisper) is designed to process audio files using various Whisper models, with options for transcription formatting, language translation and more.
---
[](https://www.runpod.io/console/hub/runpod-workers/worker-faster_whisper)
---
## 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:
```json
{
"input": {
"audio": "https://github.com/runpod-workers/sample-inputs/raw/main/audio/gettysburg.wav",
"model": "turbo"
}
}
```
producing an output like this:
```json
{
"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
}
```