Marco-Christiani/zigrad
A deep learning framework built on an autograd engine with high level abstractions and low level control.
Repository profile
Tensor library for machine learning, inspired by ggml
Repository updates
Get generated candrewlee14/zgml development summaries by email, or follow the weekly and monthly RSS feeds.
Sign in to subscribe by email. RSS feeds are public.
Sign in to subscribeTracked growth, recent movement, and commit velocity from stored repository snapshots.
Latest capture 2026-07-23 03:02
4 captures since 2026-06-09
Stars from baseline +2
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-07-23 03:02
Searchable topics, generated tags, and stack labels that explain where this repository fits.
Agent instructions and tool configuration paths found in the repository tree.
Nearest indexed repositories by embedding similarity.
A deep learning framework built on an autograd engine with high level abstractions and low level control.
Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild
Learn how LLMs work by building one in Zig -- from tensors to text generation.
Zig-based implementation of tensors
⚡ Zig-native TLS 1.3 Implementation library for edge/load-balancer event loops, with BoGo strict, interop, and reliability gates.
Zig Ethereum client library. Faster than alloy.rs on 20/26 benchmarks.