Bringing Whisper and LLaMA to the masses

The Changelog

This week we’re talking with Georgi Gerganov about his work on Whisper.cpp and llama.cpp. Georgi first crossed our radar with whisper.cpp, his port of OpenAI’s Whisper model in C and C++. Whisper is a speech recognition model enabling audio transcription and translation. Something we’re paying close attention to here at Changelog, for obvious reasons. Between the invite and the show’s recording, he had a new hit project on his hands: llama.cpp. This is a port of Facebook’s LLaMA model in C and C++. Whisper.cpp made a splash, but llama.cpp is growing in GitHub stars faster than Stable Diffusion did, which was a rocket ship itself.

This week we’re talking with Georgi Gerganov about his work on Whisper.cpp and llama.cpp. Georgi first crossed our radar with whisper.cpp, his port of OpenAI’s Whisper model in C and C++. Whisper is a speech recognition model enabling audio transcription and translation. Something we’re paying close attention to here at Changelog, for obvious reasons. Between the invite and the show’s recording, he had a new hit project on his hands: llama.cpp. This is a port of Facebook’s LLaMA model in C and C++. Whisper.cpp made a splash, but llama.cpp is growing in GitHub stars faster than Stable Diffusion did, which was a rocket ship itself.

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Featuring:

Show Notes:

Something missing or broken? PRs welcome!

Timestamps:

(00:00) - This week on The Changelog
(01:20) - Sponsor: Postman
(04:09) - Start the show!
(12:03) - Why is Whisper interesting to us?
(17:04) - What's involved in making a port?
(22:55) - Sponsor: Sentry
(24:51) - One layer deeper
(27:57) - Examples of Whisper.cpp
(31:49) - Whisper.cpp and speaker detection
(39:25) - What did you learn about Apple Silicon?
(42:26) - Apple's secret M1 coprocessor
(44:56) - GPU support on the roadmap
(47:06) - Cultivating contributions
(48:49) - Ludacris Llama Llama Red Pajama
(52:57) - What is Llama.cpp so interesting?
(57:01) - What are you going from here?
(58:22) - How can this be extended?
(1:01:22) - How did you learn this stuff?
(1:08:48) - Wrapping up
(1:10:09) - Outro

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