whisper-jax

Maintainer: alqasemy2020

Total Score

77

Last updated 5/23/2024

🌐

PropertyValue
Model LinkView on Replicate
API SpecView on Replicate
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

whisper-jax is a faster and cheaper implementation of OpenAI's Whisper model, developed by the maintainer alqasemy2020. Compared to similar models like incredibly-fast-whisper, whisper-large-v3, whisper, and whisperx, whisper-jax promises up to 15x speed-up, though it does not support TPU.

Model inputs and outputs

whisper-jax takes a single input, an audio file in a supported format. It outputs a prediction of the speech transcription in the audio.

Inputs

  • audio: An audio file in a supported format

Outputs

  • Output: The predicted speech transcription

Capabilities

whisper-jax can transcribe speech from audio files, similar to other Whisper models. It is designed to be faster and cheaper to run than the original Whisper model.

What can I use it for?

You can use whisper-jax for any project or application that requires real-time speech transcription, such as live captioning, voice-to-text conversions, or automated transcription of audio recordings. The increased speed and reduced cost of whisper-jax compared to the original Whisper model may make it more viable for commercial or enterprise-level applications.

Things to try

Try experimenting with whisper-jax on different types of audio, such as interviews, lectures, or podcasts, to see how it performs in various scenarios. You can also compare its performance and accuracy to other Whisper models, like whisper-large-v3 or whisperx, to understand its relative strengths and weaknesses.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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