AutoKeras repo skill

SkillProductivity

"Use AutoKeras for Keras-based AutoML task APIs, custom AutoModel

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the AutoKeras repo skill skill

What this skill tells your AI

The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/autokeras/SKILL.md and read by ahel’s review.

Use this skill when a user asks how to operate AutoKeras: Keras-based AutoML for image, text, structured-data, custom search-space, tuner, and export workflows. This skill is self-contained; do not rely on the original repository checkout at runtime.

Setup first

AutoKeras 3.0.0 uses Keras 3. Choose and install a Keras backend before importing Keras or AutoKeras. The repository's public install guidance and CI support a PyTorch backend path for ordinary CPU checks.

python -m pip install autokeras
python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
KERAS_BACKEND=torch python -c "import keras, autokeras as ak; print(ak.__version__, keras.backend.backend())"

Run scripts/check_autokeras_env.py when setup, backend, import, or public API visibility is uncertain.

Route by task

  • sub-skills/task-apis/SKILL.md: high-level ImageClassifier, ImageRegressor, TextClassifier, TextRegressor, StructuredDataClassifier, and StructuredDataRegressor workflows, including data shapes and task-specific troubleshooting.
  • sub-skills/automodel-customization/SKILL.md: custom AutoModel graphs, nodes, blocks, heads, multimodal inputs, multitask outputs, and graph/data ordering failures.
  • sub-skills/search-and-export/SKILL.md: tuner names/classes, max_trials, objectives, callbacks, search directories, overwrite, export_model(), and reloading saved .keras models.

Shared references

Operating constraints

  • Keep first runs bounded: max_trials=1, epochs=1, small synthetic/local data, and an explicit scratch directory.
  • Set KERAS_BACKEND before importing Keras or AutoKeras.
  • Do not run original examples, notebooks, benchmark scripts, Docker scripts, or release tooling as runtime dependencies. Use bundled scripts and references instead.
  • CUDA/GPU execution is optional for this skill. Do not claim GPU verification unless the user's own environment and backend framework have been checked.

Signals

GitHub stars
266
Forks
21
Last commit
Sep 2026

ahel review

  • K1binfo
    installs-packages
  • K6low
    bundled executables the agent is told to run
  • K1binfo
    installs-packages (in references/setup-and-troubleshooting.md)

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
autokeras
Source
github.com/vectorspacelab/arex-skill