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hnesk /whisper-wordtimestamps:a7125280

Playground API

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
model
string (enum)
base

Options:

tiny, base, small, medium, large-v1, large-v2

Choose a Whisper model.
language
string (enum)

Options:

af, am, ar, as, az, ba, be, bg, bn, bo, br, bs, ca, cs, cy, da, de, el, en, es, et, eu, fa, fi, fo, fr, gl, gu, ha, haw, he, hi, hr, ht, hu, hy, id, is, it, ja, jw, ka, kk, km, kn, ko, la, lb, ln, lo, lt, lv, mg, mi, mk, ml, mn, mr, ms, mt, my, ne, nl, nn, no, oc, pa, pl, ps, pt, ro, ru, sa, sd, si, sk, sl, sn, so, sq, sr, su, sv, sw, ta, te, tg, th, tk, tl, tr, tt, uk, ur, uz, vi, yi, yo, zh, Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Azerbaijani, Bashkir, Basque, Belarusian, Bengali, Bosnian, Breton, Bulgarian, Burmese, Castilian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Faroese, Finnish, Flemish, French, Galician, Georgian, German, Greek, Gujarati, Haitian, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Lao, Latin, Latvian, Letzeburgesch, Lingala, Lithuanian, Luxembourgish, Macedonian, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Moldavian, Moldovan, Mongolian, Myanmar, Nepali, Norwegian, Nynorsk, Occitan, Panjabi, Pashto, Persian, Polish, Portuguese, Punjabi, Pushto, Romanian, Russian, Sanskrit, Serbian, Shona, Sindhi, Sinhala, Sinhalese, Slovak, Slovenian, Somali, Spanish, Sundanese, Swahili, Swedish, Tagalog, Tajik, Tamil, Tatar, Telugu, Thai, Tibetan, Turkish, Turkmen, Ukrainian, Urdu, Uzbek, Valencian, Vietnamese, Welsh, Yiddish, Yoruba

language spoken in the audio, specify None to perform language detection
temperature
number
0
temperature to use for sampling
patience
number
optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search
suppress_tokens
string
-1
comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations
initial_prompt
string
optional text to provide as a prompt for the first window.
condition_on_previous_text
boolean
True
if True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop
temperature_increment_on_fallback
number
0.2
temperature to increase when falling back when the decoding fails to meet either of the thresholds below
compression_ratio_threshold
number
2.4
if the gzip compression ratio is higher than this value, treat the decoding as failed
logprob_threshold
number
-1
if the average log probability is lower than this value, treat the decoding as failed
no_speech_threshold
number
0.6
if the probability of the <|nospeech|> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence
word_timestamps
boolean
False
Extract word-level timestamps using the cross-attention pattern and dynamic time warping, and include the timestamps for each word in each segment.
prepend_punctuations
string
"'“¿([{-
If word_timestamps is True, merge these punctuation symbols with the next word
append_punctuations
string
"'.。,，!！?？:：”)]}、
If word_timestamps is True, merge these punctuation symbols with the previous word

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema 
{'properties': {'detected_language': {'title': 'Detected Language',
                                      'type': 'string'},
                'segments': {'title': 'Segments'},
                'transcription': {'title': 'Transcription', 'type': 'string'}},
 'required': ['detected_language', 'transcription'],
 'title': 'ModelOutput',
 'type': 'object'}