Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation, trained on 680k hours of labelled data without the need for fine-tuning. It is a Transformer based encoder-decoder model, trained on either English-only or multilingual data, and is available in five configurations of varying model sizes. The models were trained on the tasks of speech recognition and speech translation, predicting transcriptions in the same or different languages as the audio.
Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation, trained on 680k hours of labelled data without the need for fine-tuning. It is a Transformer based encoder-decoder model, trained on either English-only or multilingual data, and is available in five configurations of varying model sizes. The models were trained on the tasks of speech recognition and speech translation, predicting transcriptions in the same or different languages as the audio.
condition_on_previous_text
booleanprovide the previous output of the model as a prompt for the next window
Default value: true
temperature_increment_on_fallback
numbertemperature to increase when falling back when the decoding fails to meet either of the thresholds below
Default value: 0.2
webhook
fileThe webhook to call when inference is done, by default you will get the output in the response of your inference request