extract-hyperparameters
Identify and document model hyperparameters from papers. Use when setting up training configurations.
npx skills add majiayu000/claude-skill-registry --skill extract-hyperparameters-homericintelligence-projectodyssey-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Extract Hyperparameters Locate and document all hyperparameters mentioned in research papers including learning rates, batch sizes, and model configurations. ## When to Use - Reproducing paper results - Setting up model training configurations - Comparing hyperparameter choices across papers - Planning hyperparameter tuning experiments ## Quick Reference ```bash # Extract numeric values and parameters from papers pdftotext paper.pdf - | grep -i "learning rate\|batch\|epochs\|weight decay\|dropout" | head -20 # Common pattern search grep -E "\\b(lr|batch_size|epochs|momentum|dropout|layers)\\s*[=:]" config.py ``` ## Workflow 1. **Find hyperparameter table**: Look for "Table 1" or "Hyperparameters" section 2. **Document architecture parameters**: Layer sizes, activation functions, normalization 3. **Extract training parameters**: Learning rate, batch size, epochs, optimizers 4. **Note regularization**: Dropout, weight decay, batch normalization 5. **Create configuration file**: Translate to implementation format (YAML/JSON/Mojo) ## Output Format Hyperparameter documentation: - Model architecture (layers, sizes, activations) - Training parameters (LR, batch size, epochs) - Optimizer
- When to Use
- Quick Reference
- Workflow
- Output Format
- References
Extract numeric values and parameters from papers pdftotext paper.pdf - | grep -i "learning rate\|batch\|epochs\|weight decay\|dropout" | head -20 Common pattern search grep -E "\\b(lr|batch_size|epochs|momentum|dropout|layers)\\s*[=:]" config.py
What does the extract-hyperparameters skill do?
Identify and document model hyperparameters from papers. Use when setting up training configurations.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill extract-hyperparameters-homericintelligence-projectodyssey-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.