newsReddit r/MachineLearningTrust 72 · CommunityPublished 1mo agoLive · 1mo ago
Kuma: compiling PyTorch models into self-contained WebGPU executables [P]
I've been experimenting with a compiler/runtime project that I'm not entirely sure is a good idea, so I'd love some feedback from people who've worked on deployment systems. The idea is to compile an exported PyTorch model into a self-contained package that contains: graph binary weights backend kernels (currently WGSL) runtime metadata A lightweight runtime loads that package and executes it directly
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 48%openinfer-project/openinfer →
- PossiblePossibly related (embedding) · 47%kyegomez/BitNet →
- PossiblePossibly related (embedding) · 51%meta-pytorch/tnt →
- PossiblePossibly related (embedding) · 48%LaurentMazare/tch-rs →
- PossiblePossibly related (embedding) · 47%d9d-project/d9d →
- PossiblePossibly related (embedding) · 48%Cambridge-ICCS/FTorch →
