AI agent that designs, trains, and iterates on the model itself — the core differentiator of any AI product. Use this skill to: design model architectures for specific tasks, fine-tune foundation models with LoRA/QLoRA/full fine-tuning, implement distributed training across multiple GPUs, build training loops with proper loss functions and optimization schedules, select and evaluate base models for transfer learning, implement data augmentation strategies, design model ensembles, optimize model size for deployment constraints, debug training failures like loss divergence or gradient explosion, or make any decision about how the model is built. Trigger on "model training", "fine-tuning", "LoRA", "QLoRA", "PyTorch", "TensorFlow", "JAX", "model architecture", "distributed training", "transfer learning", "loss function", "optimizer", "learning rate", "gradient", "PEFT", "foundation model", "base model", "model selection", or when the AI model itself needs to be designed, trained, or improved.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryEngineeringStars0
About this skill
AI agent that designs, trains, and iterates on the model itself — the core differentiator of any AI product. Use this skill to: design model architectures for specific tasks, fine-tune foundation models with LoRA/QLoRA/full fine-tuning, implement distributed training across multiple GPUs, build training loops with proper loss functions and optimization schedules, select and evaluate base models for transfer learning, implement data augmentation strategies, design model ensembles, optimize model size for deployment constraints, debug training failures like loss divergence or gradient explosion, or make any decision about how the model is built. Trigger on "model training", "fine-tuning", "LoRA", "QLoRA", "PyTorch", "TensorFlow", "JAX", "model architecture", "distributed training", "transfer learning", "loss function", "optimizer", "learning rate", "gradient", "PEFT", "foundation model", "base model", "model selection", or when the AI model itself needs to be designed, trained, or improved.
Quick start
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AI agent that designs, trains, and iterates on the model itself — the core differentiator of any AI product. Use this skill to: design model architectures for specific tasks, fine-tune foundation models with LoRA/QLoRA/full fine-tuning, implement distributed training across multiple GPUs, build training loops with proper loss functions and optimization schedules, select and evaluate base models for transfer learning, implement data augmentation strategies, design model ensembles, optimize model size for deployment constraints, debug training failures like loss divergence or gradient explosion, or make any decision about how the model is built. Trigger on "model training", "fine-tuning", "LoRA", "QLoRA", "PyTorch", "TensorFlow", "JAX", "model architecture", "distributed training", "transfer learning", "loss function", "optimizer", "learning rate", "gradient", "PEFT", "foundation model", "base model", "model selection", or when the AI model itself needs to be designed, trained, or improved.
About this listing
Category
Engineering
Reported license
MIT
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.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI