---
title: "apple/coreai-models skills · skilld"
canonical_url: "https://skilld.dev/gh/apple/coreai-models"
meta:
description: "Model export recipes, Python primitives, and Swift runtime utilities for on-device AI"
"og:description": "Model export recipes, Python primitives, and Swift runtime utilities for on-device AI"
"og:title": "apple/coreai-models skills"
"twitter:description": "Model export recipes, Python primitives, and Swift runtime utilities for on-device AI"
"twitter:title": "apple/coreai-models skills"
---
`
[All skills](https://skilld.dev/skills)
[](https://skilld.dev/gh/apple)
# **apple/coreai-models**
Model export recipes, Python primitives, and Swift runtime utilities for on-device AI
main Updated 2 hours ago [GitHub](https://github.com/apple/coreai-models)
## Repository statistics
- Indexed skills
**3**
- Skill groups
**1**
- GitHub stars
**2,164**
- Forks
**219**
## Skills
3 total
Sort skills
[
**/working-with-coreai**
Use this skill whenever the user mentions coreai-torch, TorchConverter, coreai-build, AIModel, AIProgram, .aimodel, or wants to export/compile/run a PyTorch model on Apple silicon (iPhone, iPad, Mac). Also triggers for "deploy on device", "optimize for on-device performance", onboarding new models to Core AI, or choosing between iOS and macOS deployment paths. /working-with-coreai](https://skilld.dev/gh/apple/coreai-models/working-with-coreai)
Updated 3 days ago
[
**/model-authoring**
Empirical rules for authoring PyTorch models for on-device execution on Apple platforms, covering energy-efficient inference, scalable compute, and correctness testing. Use this skill whenever the user is writing, debugging, or reviewing PyTorch model code intended for on-device execution — even if they don't explicitly mention Neural Engine or Core AI. Covers BC1S layout, op compatibility, KV cache patterns, precision rules, PSNR verification, activation functions, and common issues. /model-authoring](https://skilld.dev/gh/apple/coreai-models/model-authoring)
Updated 4 months ago
[
**/model-compression-exploration**
Systematically explore weight compression configurations (quantization and palettization) for a PyTorch model using coreai-opt, presenting a comprehensive overview of accuracy-vs-size tradeoff options. Use this skill whenever the user wants to compress a model, explore quantization or palettization options, understand compression config tradeoffs, reduce model size, or compare different compression techniques. Also trigger when the user mentions coreai-opt compression, weight quantization exploration, or palettization exploration — even if they don't say "explore" explicitly. /model-compression-exploration](https://skilld.dev/gh/apple/coreai-models/model-compression-exploration)
Updated 4 months ago
## Add to your README
The badge links readers to this page. It shows the skilld mark and no counts, and it follows the reader's light or dark GitHub theme.
``