Fast Whisper Turbo

Fast Whisper Turbo

Runs OpenAI's whisper-large-v3-turbo speech recognition model in a Gradio app built for quick transcription. It suits anyone who needs audio turned into text and developers who want a short Whisper wrapper to read.

Made by mrfakename on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: Fast Whisper Turbo is a Gradio app that runs the openai/whisper-large-v3-turbo speech recognition model. Its tagline promises extra quick Whisper Turbo inference. The repository is small, with just a README, app.py and requirements.txt.

Who it suits: People who need spoken audio turned into text without setting up a speech model themselves.

Industry | Who uses it | How they use it | Example
Media | Podcasters | Get a transcript of an episode | A recorded interview
Education | Students | Turn lecture recordings into notes | A lecture clip
Software | Developers | Read a short Gradio wrapper around a Whisper model | Opening app.py
Research | Interviewers | Convert field recordings into text | A voice memo

If you never work with recorded speech, you can skip it.

Where to use it:

• A web browser, on the Space's page at Hugging Face
• Windows, macOS or Linux with Python, from a downloaded copy

Use case | Who | What they get back
Transcribing audio | Anyone with recordings | The spoken words as written text
Code reading | Developers | A small Whisper app they can study and change

How to set it up:

• Python on your computer
• Python packages from requirements.txt, with Gradio 6.30.0
• At Hugging Face the Space runs on zero-a10g hardware, so a copy may want a similar GPU

1. Install the Hugging Face hub package.
2. Download the Space with the hf command.
3. Move into the downloaded folder.
4. Install Gradio 6.30.0, then the requirements.
5. Start app.py.

pip install -U huggingface_hub
hf download mrfakename/fast-whisper-turbo --repo-type space --local-dir fast-whisper-turbo
cd fast-whisper-turbo
pip install gradio==6.30.0
pip install -r requirements.txt
python app.py

How to use it: Online, open the Space page and use the screen there. On your own computer, start the app with the command below and use the screen it opens.

python app.py

Example: You give the app a short recording of someone speaking and run it. The source does not show the screen, but a Whisper app of this kind returns the spoken words as text.

For newcomers and experts: Whisper is OpenAI's speech to text model. Open the Space page, give it one short clip and read what comes back.

The app names openai/whisper-large-v3-turbo as its model and runs on zero-a10g hardware at Hugging Face. The source gives no speed figures and no option list, so judge the speed claim by trying it.

You give the app an audio clip
app.py passes it to the Whisper model
The model decodes the speech
The text is shown on the screen

Good to know:

• Hardware: zero-a10g at Hugging Face, built with Gradio 6.30.0
• License: apache-2
• Cost to run: none named
• Data it reaches: the audio you give it, nothing else named
• Not for: the source names no limits

On Hugging Face, 13 November 2026

• Likes: 58
• Built with: gradio
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/mrfakename/fast-whisper-turbo
• Files: https://huggingface.co/spaces/mrfakename/fast-whisper-turbo/tree/main

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.