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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
string (enum)
transcribe

Options:

transcribe, translate

Task to perform: transcribe or translate to another language.
language
string (enum)
None

Options:

None, afrikaans, albanian, amharic, arabic, armenian, assamese, azerbaijani, bashkir, basque, belarusian, bengali, bosnian, breton, bulgarian, cantonese, catalan, chinese, croatian, czech, danish, dutch, english, estonian, faroese, finnish, french, galician, georgian, german, greek, gujarati, haitian creole, hausa, hawaiian, hebrew, hindi, hungarian, icelandic, indonesian, italian, japanese, javanese, kannada, kazakh, khmer, korean, lao, latin, latvian, lingala, lithuanian, luxembourgish, macedonian, malagasy, malay, malayalam, maltese, maori, marathi, mongolian, myanmar, nepali, norwegian, nynorsk, occitan, pashto, persian, polish, portuguese, punjabi, romanian, russian, sanskrit, serbian, shona, sindhi, sinhala, slovak, slovenian, somali, spanish, sundanese, swahili, swedish, tagalog, tajik, tamil, tatar, telugu, thai, tibetan, turkish, turkmen, ukrainian, urdu, uzbek, vietnamese, welsh, yiddish, yoruba

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
string (enum)
chunk

Options:

chunk, word

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'}