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vaibhavs10 /incredibly-fast-whisper:3ab86df6
Input schema
The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.
| Field | Type | Default value | Description |
|---|---|---|---|
| audio |
string
|
Audio file
|
|
| task |
None
|
transcribe
|
Task to perform: transcribe or translate to another language.
|
| language |
None
|
None
|
Language spoken in the audio, specify 'None' to perform language detection.
|
| batch_size |
integer
|
24
|
Number of parallel batches you want to compute. Reduce if you face OOMs.
|
| timestamp |
None
|
chunk
|
Whisper supports both chunked as well as word level timestamps.
|
| diarise_audio |
boolean
|
False
|
Use Pyannote.audio to diarise the audio clips. You will need to provide hf_token below too.
|
| hf_token |
string
|
Provide a hf.co/settings/token for Pyannote.audio to diarise the audio clips. You need to agree to the terms in 'https://huggingface.co/pyannote/speaker-diarization-3.1' and 'https://huggingface.co/pyannote/segmentation-3.0' first.
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'title': 'Output'}