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rHedBull AI Skills

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浏览 rHedBull 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。

作者统计

已收录技能

8

收录技能的仓库 Stars 合计

0

仓库 Forks

0

平均每个技能的仓库 Stars

0

同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。

8 个技能

全部技能

GitHub

hyperparam-sweep

rHedBull

Systematically search hyperparameter space. Use when tuning learning rate, batch size, or other hyperparameters.

GitHub

train-debug

rHedBull

Interactive diagnostic workflow for training problems. Use when training is failing, loss is stuck, gradients explode, NaN occurs, or convergence is poor.

GitHub

train

rHedBull

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

rHedBull

Design rigorous experiments before running them. Use when planning experiments, testing hypotheses, or designing ablation studies.

GitHub

monitor

rHedBull

View training progress in real-time. Use when checking on running training, viewing live metrics, or opening dashboards.

GitHub

run-validation

rHedBull

Run model validation on a dataset. Use when testing model performance, comparing checkpoints, or running final evaluation.

GitHub

interpret-curves

rHedBull

Analyze training logs and explain what's happening. Use when reviewing training runs, understanding loss curves, or diagnosing completed training.

GitHub

scaling-analysis

rHedBull

Run scaling experiments to understand model/data/compute relationships. Use when investigating scaling laws, compute-optimal training, or model size decisions.

默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。