neuron-explorer
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
Free, open-source tool that shrinks the memory a local AI model uses on your Mac — up to 16×, in three lines of code. Runs entirely on your machine.
Developer toolsPython · CSSGitHub @rajveer43OnlineOwner unconfirmed
Have you tried it? One tap is enough. No sign-in needed.
Fast KV-cache quantization for Apple Silicon (MLX) — 43 research-adapted compression methods with Metal kernels
Taken from the repository README
Loading the full README. The saved excerpt is shown below.
43 compression methods — quantizers, token-eviction caches, cross-layer merging — in MLX
VeloxQuant-MLX shrinks the KV cache of any mlx_lm model on Apple Silicon, up to 16× smaller with near-lossless quality, in three lines of code. If you run models locally and keep hitting a context-length or memory wall, you swap in a compressed cache and change nothing else about the model.Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
43 compression methods — quantizers, token-eviction caches, cross-layer merging — in MLX
VeloxQuant-MLX shrinks the KV cache of any mlx_lm model on Apple Silicon, up to 16× smaller with near-lossless quality, in three lines of code. If you run models locally and keep hitting a context-length or memory wall, you swap in a compressed cache and change nothing else about the model.Read the full README ↗