ml-research-lab
byanastasiyaw· 37 skills
Machine-learning research loop for dataset curation, fine-tuning, evaluation, inference deployment, experiment tracking, and model explainability. Use when working on ML experiments, training data, model benchmarks, RunPod/GPU runs, classifier quality, vLLM/GGUF serving, SHAP-style model explanations, or research-to-code iterations. Do not use for a simple code edit that has no ML dataset, metric, model, or experiment artifact.
How to install ml-research-lab?
anastasiyaw/claude-code-config/ml-research-lab
$npx -y skills add anastasiyaw/claude-code-config --skill ml-research-labInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/anastasiyaw/claude-code-config" --skill "anastasiyaw/claude-code-config/ml-research-lab"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/anastasiyaw/claude-code-config" that are relevant to the current task. Run `npx skills add "https://github.com/anastasiyaw/claude-code-config"` and select the relevant skills, then follow their instructions.
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