Pre-trained Neural Network models in Axon (+ 🤗 Models integration)
-
Updated
Jul 22, 2026 - Elixir
Pre-trained Neural Network models in Axon (+ 🤗 Models integration)
TRINITY in Elixir (An Evolved LLM Coordinator): route LLM calls via a small-model hidden-state router + Axon coordination head, with Thinker/Worker/Verifier orchestration and policy loop for acceptance-driven completion.
Computer Vision :: Digits recognition fullstack machine learning application using Nx, Axon, and LiveView :: MNIST dataset
Bumblebee, Axon, and Nx adapter layer for compiling Crucible tap plans into model runs, hooks, traces, and decode steering.
Routing, gating, fusion, uncertainty, verifier, shared memory, and steering decision contracts over Crucible signal traces.
Composable regularization penalties for Elixir Nx. L1/L2/Elastic Net, KL divergence, entropy, consistency, gradient penalty, orthogonality. Pure Nx.Defn for JIT across EXLA/Torchx. Pipeline composition and Axon.Loop integration.
Tap-plan and probe-contract library for selecting, bounding, and negotiating model-internal forward-pass observations.
Bounded forward-pass trace schema and persistence helpers for Crucible signal captures, layer trajectories, and decode telemetry.
Canonical Elixir signal ontology for transformer forward-pass artifacts, tensor summaries, capabilities, and internal-control surfaces.
Opsmaru AI Models for DevOps / Platform Engineering
Add a description, image, and links to the axon topic page so that developers can more easily learn about it.
To associate your repository with the axon topic, visit your repo's landing page and select "manage topics."