pymss-core

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Core model, configuration, and checkpoint package for music source separation.

pymss-core is the shared low-level package for higher-level projects such as pymss inference and pymsst training. It contains model definitions, configuration loading, and checkpoint compatibility helpers. It intentionally does not include inference DSP pipelines, chunked demixing, audio file I/O, model downloads, catalog management, CLI, HTTP server, WebUI, datasets, losses, or training loops.

Install

pip install pymss-core

For local development:

uv sync --dev

Optional MLX backend on Apple Silicon:

pip install "pymss-core[mlx]"

Public API

from pymss_core import (
    get_model_from_config,
    load_config,
    load_model_weights,
)

model, config = get_model_from_config("bs_roformer", "config.yaml")
load_model_weights(model, "model.ckpt", model_type="bs_roformer", strict=True)

model.eval()

Package Boundary

Included:

  • YAML config loading with AttrDict
  • PyTorch model definitions under pymss_core.modules
  • Optional MLX backend implementations for supported model forward paths
  • Model factory: get_model_from_config(model_type, config_path)
  • Checkpoint helpers for common MSS checkpoint containers
  • Small model-internal DSP math needed to construct model structures
  • VR network structures and VR model parameter JSON files

Excluded:

  • Audio file decoding/encoding
  • Resampling, preprocessing, and full inference DSP pipelines
  • Tensor-level chunked demixing runtime
  • Model catalog, aliases, downloads, and cache management
  • CLI, server, WebUI, and endpoint schemas
  • Dataset, augmentation, loss, metrics, and trainer code
  • Any default dependency on MLX, Librosa, tqdm, Lightning, FastAPI, Uvicorn, PyAV, WandB, or training extras

Repository Roles

pymss-core
  shared model/config/checkpoint layer

pymss
  user-facing inference package built on pymss-core, with audio I/O and demix

pymsst
  training package built on pymss-core, with training data/loss/runtime code

Project links

Data verified by PyPI on Jun 30, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (0.1.6)

1 maintainer

PyPI data
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Avatar for baicai1145 from gravatar.com baicai1145

Credits

Author: KitsuneX07

Maintainer: baicai1145

GitHub Statistics

Data verified by PyPI on Jun 30, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.10

Provides Extra

mlx

Tags

music source separation audio separation music processing machine learning audio

Classifiers

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