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lightningrod-python-sdk
Generate forecasting datasets and fine-tune models using the Lightningrod Python SDK. Create seed data from BigQuery public datasets, local files, or web searches; build SFT and GRPO training data; track experiments; and run transform pipelines for forecasting model development.
What's Inside
Skills10
bigquery-seeds
/bigquery-seeds
BigQuery seed sourcing patterns for Lightningrod. Use when sourcing seeds from BigQuery tables.
content-learning-examples
/content-learning-examples
Production examples for content learning (SFT) training -- survival field guide (TopicTree + WebSearch), medical textbooks (FileSet + QuestionAndLabel). Use when teaching domain knowledge via Q&A pairs and SFT.
custom-dataset-seeds
/custom-dataset-seeds
Seed generation from user-provided files and custom datasets. Use when converting local files, CSVs, PDFs, or user uploads into Lightningrod seeds.
examples-guide
/examples-guide
Decision tree for choosing a training pattern (forward-looking GRPO, content learning SFT, tabular data). Use when starting a new project, choosing between RL and SFT, or selecting an answer type.
experiment-tracking
/experiment-tracking
Standardised training-experiment tracking. One notebook per experiment under `./userland/<project>/experiments/`, plus a single `experiments.md` index table at the project root. Use whenever a training run's tracked config differs from the previous run.
Stats
Version1.0.0
LanguageJupyter Notebook
Stars51
Forks4
MaintenanceExcellent
LicenseMIT
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Uses power tools
Uses Bash, Write, or Edit tools
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