microduck / NOTICE.md
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Publish MicroDuck FastWAM inference weights and pinned dependencies
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Artifact provenance and third-party notices

This is the inference-file release for https://github.com/fuheaven/LightX2V-microduck.

Project-trained navigation checkpoint

  • Original run: clear-room-realtime-control-pilot-v1, step 250.
  • Exact model SHA256: 8ea7793290f0a22bff56ec4e44168232564ec5d57a9e21515a8a8c4a989114ea.
  • The original normalization and checkpoint receipt are preserved byte for byte.
  • A separate license for these project-specific weights has not been designated by the owner. The presence of third-party license texts below is not a blanket license assignment to these weights.
  • Hardware status: hardware_unvalidated. Published numbers are simulation development evidence, not independent full acceptance.

Wan inference components

Implementation and research attribution

  • LightX2V: https://github.com/ModelTC/LightX2V, Apache-2.0.
  • FastWAM: https://github.com/yuantianyuan01/FastWAM, MIT source license retained as licenses/FastWAM-MIT.txt.
  • The Python inference implementation, Docker build, simulator, tests, and evidence are distributed by the linked code repository. This model repository does not ship training optimizer states or an executable Python pickle loader beyond the original model serialization.

Separately downloaded simulator dependencies