distil-whisper VS setfit

Training code will be released in the Distil-Whisper repository this week, enabling anyone in the community to distill a Whisper model in their choice of language!

Hugging Face released Distil-Whisper, a distilled version of Whisper that is 6 times faster, 49% smaller, and performs within 1% word error rate (WER) on out-of-distribution evaluation sets [Details].

- GitHub page: https://github.com/huggingface/distil-whisper/tree/main

Is https://github.com/huggingface/distil-whisper on its way to whisper.cpp?

It did, sorry for the hasty edits! I removed that part b/c I realized that there isn't a compelling-enough reason for me to believe that text similarity is clearly inappropriate. In fact, you can train the Pr(condition | chat) classifier I suggested above using similarity training! Use SetFit for that. In the end you'll get a classifier and a similarity model.

[3] https://github.com/huggingface/setfit

There's also kinda related approaches like SetFit which calculate embeddings from pretrained transformer models then then fit a classifier on top of the embeddings. I've yet to try it but it supposedly works well with very few labelled examples.

You could have a look at setfit.

Found relevant code at https://github.com/huggingface/setfit + all code implementations here

Efficient Few-Shot Learning Without Prompts https://github.com/huggingface/setfit https://arxiv.org/abs/2209.11055v1