WAAS VS modal-examples

This app does it locally on newer macs for free.

https://apps.apple.com/no/app/jojo-transcribe/id1659864300?m...

And open source: https://github.com/schibsted/WAAS

Clone the repo, then run the steps in the dockerfile: https://github.com/schibsted/WAAS/blob/main/Dockerfile

What utilities related to Whisper do you wish existed? What have you had to build yourself?

On the end user application side, I wish there was something that let me pick a podcast of my choosing, get it fully transcribed, and get an embeddings search plus answer q&a on top of that podcast or set of chosen podcasts. I've seen ones for specific podcasts, but I'd like one where I can choose the podcast. (Probably won't build it)

Also on the end user side, I wish there was an Otter alternative (still paid $30/mo, but unlimited minutes per month) that had longer transcription limits. (Started building this, not much interest from users though)

Things I've seen on the dev tool side:

Gladia (API call version of Whisper)

Whisper.cpp

Whisper webservice (https://github.com/ahmetoner/whisper-asr-webservice) - via this thread

Live microphone demo (not real time, it still does it in chunks) https://github.com/mallorbc/whisper_mic

Streamlit UI https://github.com/hayabhay/whisper-ui

Whisper playground https://github.com/saharmor/whisper-playground

Real time whisper https://github.com/shirayu/whispering

Whisper as a service https://github.com/schibsted/WAAS

Improved timestamps and speaker identification https://github.com/m-bain/whisperX

MacWhisper https://goodsnooze.gumroad.com/l/macwhisper

Crossplatform desktop Whisper that supports semi-realtime https://github.com/chidiwilliams/buzz

We made a small app for SDXL Lightning, running your own Python code on GPUs. It generates images in real time.

https://potatoes.ai/

We know there was a fal.ai post yesterday, and that got a lot of interest, but we also made this demo yesterday and didn't share — just wanted to mention it as an alternative option for people who like running their own code and custom models instead of using a prebuilt API provider.

The backend code is open-source too and you can deploy it yourself: https://github.com/modal-labs/modal-examples/blob/main/06_gpu_and_ml/stable_diffusion/stable_diffusion_xl_lightning.py

The startup I work at is relatively pretty good at documentation engineering. We have written code to test the code snippets in docstrings (https://github.com/modal-labs/pytest-markdown-docs) and we have written code to do synthetic monitoring testing of the examples in our examples repo (https://github.com/modal-labs/modal-examples). We are also diligent about putting using Python's warnings library to handle API deprecation, and treat deprecation warnings as errors internally, ensuring our own code samples and examples are most up-to-date.

You can get it running with one Python script on Modal.com :)

https://github.com/modal-labs/modal-examples/blob/main/06_gp...

This demo lets you choose the podcast, and is open-source: https://modal-labs--whisper-pod-transcriber-fastapi-app.moda...

https://github.com/modal-labs/modal-examples/tree/main/06_gp...

Transcribes 1hr of audio in roughly 1min, using parallelisation across CPUs.

This demo is open-source: https://github.com/modal-labs/modal-examples/tree/main/06_gp....

https://modal-labs--whisper-pod-transcriber-fastapi-app.moda...

It's become so easy to stick together ML models, often without training most or all of them yourself.

*video demo:* https://youtu.be/mQsMuM8d4Qc

*cloud platform:* https://modal.com

*code*: https://github.com/modal-labs/modal-examples/tree/main/06_gp...

Transcription - OpenAI just released Whisper. Check out what it can do with podcasts

Here's the source code.