GitHub
hyperparam-sweep
Systematically search hyperparameter space. Use when tuning learning rate, batch size, or other hyperparameters.
rHedBull AI Skills
GitHub ↗Explorez les skills IA publiés de rHedBull et consultez leurs instructions source.
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Skills indexés
8Étoiles des dépôts des skills indexés
0Forks du dépôt
0Moyenne des étoiles par skill indexé
0Les étoiles d’un dépôt peuvent se répéter entre ses skills.
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GitHub
train-debug
Interactive diagnostic workflow for training problems. Use when training is failing, loss is stuck, gradients explode, NaN occurs, or convergence is poor.
GitHub
train
Execute a neural network training run with mandatory monitoring and best-practice defaults. Use when user wants to train a model, start training, or run a training job.
GitHub
experiment-plan
Design rigorous experiments before running them. Use when planning experiments, testing hypotheses, or designing ablation studies.
GitHub
monitor
View training progress in real-time. Use when checking on running training, viewing live metrics, or opening dashboards.
GitHub
run-validation
Run model validation on a dataset. Use when testing model performance, comparing checkpoints, or running final evaluation.
GitHub
interpret-curves
Analyze training logs and explain what's happening. Use when reviewing training runs, understanding loss curves, or diagnosing completed training.
GitHub
scaling-analysis
Run scaling experiments to understand model/data/compute relationships. Use when investigating scaling laws, compute-optimal training, or model size decisions.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.