
u/maximecb

Building Groovie, an Advanced Web-Based Drum Machine / Beat Sequencer
pointersgonewild.comGroovie: an advanced web-based drum machine / beat sequencer that's fully free and can output a MIDI clock signal
Hi there! Just wanted to share an open source music project I've been working on. There are already a number of web-based drum machines, but I think most of them are pretty basic (small fixed drum kit, single pattern, etc), so I built something more advanced.
I'm calling it Groovie, and notably, it has a timeline view so you can arrange up to 32 patterns into a song. It has 150+ samples you can select from. You can adjust the panning and volume of each row individually. It has delay as well as an LPF/HPF filter and swing. It has the ability to send a MIDI clock signal so you can sync it with your hardware (Chrome only), and lastly, it works on mobile phones and tablets too. I designed the interface to be intuitive and to use fairly standard design language (I hate cryptic UIs).
The app is fully static with no backend, but you can share beats/tracks with others as they can be encoded into the hash part of a link, in a compressed format. Some examples:
The app is live here: https://maximecb.github.io/groovie
The GitHub repo: https://github.com/maximecb/groovie
Since it's open source and fully static, it's free forever. You don't need any kind of account to use it. You can't upload new samples in the app, but I am very much open to accepting contributions (pull requests) for new samples, but they have to be public domain / CC0 / out of copyright.
Let me know what you think. If anybody wants to share some patterns they create, I would love to add them as new examples in the readme.
I Want to Build a Sandboxed, Cross-Platform Software Distribution System
pointersgonewild.comI put together a Rust-native, CPU-only implementation of LFM2.5-8B-A1B
This is still a work in progress, but since recording the video, I added callbacks for tool use, more tests, and published it as a cargo crate. Currently working on speeding up the prefill.
The decode speed is almost the same on my Ryzen 7950x (~37 tokens/s), but the prefill speed is not yet optimized (almost the same as decode).
This model can comfortably run on a machine with 16GB of RAM. Its memory usage will fit within ~7GB. You can reuse the weights between multiple Agent instances, each with their own KV cache. You can also clone Agent object instances if your agents have the same prompt so that you don't need to repeat the prefill work on the prompt.
The GitHub repo is here: https://github.com/maximecb/bebelm