The examples/ directory contains comprehensive examples demonstrating various usage patterns:
| Example | Description |
|---|---|
00_quick_start.py |
Basic model loading and testing |
01_basic_model_loading.py |
Loading pre-trained models with checkpoints and class mappings |
02_checkpoint_loading.py |
Working with default and custom checkpoints from YAML configs |
03_custom_model_registration.py |
Creating and registering custom model classes and ModelSpecs |
04_training_and_evaluation.py |
Full training loop and evaluation examples |
05_embedding_extraction.py |
Feature extraction with return_features_only=True (unpooled features) |
06_classifier_head_loading.py |
Understanding classifier head behavior with different num_classes settings |
colab_sl_beats_demo.ipynb |
Google Colab demo for the sl-beats model |
avex/
├── __init__.py # Main API exports and version
├── api/ # Public API layer
│ ├── configs/ # Official model configurations
│ │ └── official_models/ # YAML configs for official models
│ └── list_models.py # CLI utility for listing models
├── cli.py # Command-line interface
├── configs.py # Pydantic configuration models
├── data/ # Data loading and processing
├── evaluation/ # Evaluation utilities
├── metrics/ # Evaluation metrics
├── models/ # Model implementations
│ ├── utils/ # Model utilities (factory, load, registry)
│ ├── probes/ # Probe implementations
│ ├── beats/ # BEATs model components
│ ├── eat/ # EAT model components
│ └── atst_frame/ # ATST-Frame model components
├── preprocessing/ # Audio preprocessing
├── training/ # Training utilities
├── utils/ # Utility functions
├── run_train.py # Training entry point
└── run_evaluate.py # Evaluation entry point
# Run all tests
uv run pytest
# Run specific test categories
uv run pytest tests/unittests/
uv run pytest tests/integration/
uv run pytest tests/consistency/
# Run with coverage
uv run pytest --cov=avex