CLI Reference¶
Each project provides a CLI for training and evaluation.
BankChurn¶
python -m bankchurn.cli train --config configs/config.yaml
python -m bankchurn.cli predict --input data/sample.json
python -m bankchurn.cli evaluate --model models/model.joblib
NLPInsight¶
python -m nlpinsight.cli train --config configs/config.yaml
python -m nlpinsight.cli predict --text "Strong quarterly earnings"
Common Options¶
| Flag | Description |
|---|---|
--config |
Path to YAML config file |
--model |
Path to model artifact |
--verbose |
Enable debug logging |
Scripts¶
| Script | Purpose |
|---|---|
scripts/setup_demo_models.sh |
Generate demo model artifacts |
scripts/run_experiments.py |
Run MLflow experiments (9 runs) |
scripts/train_production_models.py |
Train all 3 models with MLflow |
scripts/benchmark_optimizations.py |
Performance benchmarks |
Last Updated: March 2026