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Model Hyperparameter Transfer and Tuning

Agent skill
1 skill

Use when you have a trained baseline GNN model with established hyperparameters (dropout rate, learning rate, epochs, optimizer settings) and want to evaluate whether alternative message-passing GNN architectures (Graph Attention Networks, Message-Passing Neural Networks) achieve comparable or.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryEngineeringStars0

About this skill

Use when you have a trained baseline GNN model with established hyperparameters (dropout rate, learning rate, epochs, optimizer settings) and want to evaluate whether alternative message-passing GNN architectures (Graph Attention Networks, Message-Passing Neural Networks) achieve comparable or.

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
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Content SHA-256: 11e952a33b7f58d0ac81c0c68b28970e37937691cb014d010d6b2b44e0663442

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About this listing

Category
Engineering
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.