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vaibhavs10/incredibly-fast-whisper
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whisper-large-v3, incredibly fast, powered by Hugging Face Transformers! 🤗
Capabilities
No capability data available
Cost
Community model (estimated from hardware time)
Input Parameters
| Name | Type | Description | Default | Constraints |
|---|---|---|---|---|
audio* | string(uri) | Audio file | — | — |
batch_size | integer | Number of parallel batches you want to compute. Reduce if you face OOMs. | 24 | — |
diarise_audio | boolean | Use Pyannote.audio to diarise the audio clips. You will need to provide hf_token below too. | false | — |
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. | — | — |
language | string | Language spoken in the audio, specify 'None' to perform language detection. | "None" | Noneafrikaansalbanianamharicarabicarmenianassameseazerbaijanibashkirbasquebelarusianbengalibosnianbretonbulgariancantonesecatalanchinesecroatianczechdanishdutchenglishestonianfaroesefinnishfrenchgaliciangeorgiangermangreekgujaratihaitian creolehausahawaiianhebrewhindihungarianicelandicindonesianitalianjapanesejavanesekannadakazakhkhmerkoreanlaolatinlatvianlingalalithuanianluxembourgishmacedonianmalagasymalaymalayalammaltesemaorimarathimongolianmyanmarnepalinorwegiannynorskoccitanpashtopersianpolishportuguesepunjabiromanianrussiansanskritserbianshonasindhisinhalaslovaksloveniansomalispanishsundaneseswahiliswedishtagalogtajiktamiltatarteluguthaitibetanturkishturkmenukrainianurduuzbekvietnamesewelshyiddishyoruba |
task | string | Task to perform: transcribe or translate to another language. | "transcribe" | transcribetranslate |
timestamp | string | Whisper supports both chunked as well as word level timestamps. | "chunk" | chunkword |
audiorequiredstringAudio file
batch_sizeintegerNumber of parallel batches you want to compute. Reduce if you face OOMs.
Default:
24diarise_audiobooleanUse Pyannote.audio to diarise the audio clips. You will need to provide hf_token below too.
Default:
falsehf_tokenstringProvide 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.
languagestringLanguage spoken in the audio, specify 'None' to perform language detection.
Default:
"None"Noneafrikaansalbanianamharicarabicarmenianassameseazerbaijanibashkirbasquebelarusianbengalibosnianbretonbulgariancantonesecatalanchinesecroatianczechdanishdutchenglishestonianfaroesefinnishfrenchgaliciangeorgiangermangreekgujaratihaitian creolehausahawaiianhebrewhindihungarianicelandicindonesianitalianjapanesejavanesekannadakazakhkhmerkoreanlaolatinlatvianlingalalithuanianluxembourgishmacedonianmalagasymalaymalayalammaltesemaorimarathimongolianmyanmarnepalinorwegiannynorskoccitanpashtopersianpolishportuguesepunjabiromanianrussiansanskritserbianshonasindhisinhalaslovaksloveniansomalispanishsundaneseswahiliswedishtagalogtajiktamiltatarteluguthaitibetanturkishturkmenukrainianurduuzbekvietnamesewelshyiddishyoruba
taskstringTask to perform: transcribe or translate to another language.
Default:
"transcribe"transcribetranslate
timestampstringWhisper supports both chunked as well as word level timestamps.
Default:
"chunk"chunkword
Version:
3ab86df6c8f5Updated: 7/25/202626.4M runs
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