LibreAlexNet -- third-party attribution
========================================

Source: https://github.com/pytorch/vision
Commit: 336d36e8db990a905498c73933e35231876e28bc (torchvision v0.26.0)
License: BSD-3-Clause
Copyright (c) Soumith Chintala 2016

The native AlexNet graph in nn.py is derived from torchvision's AlexNet
implementation. It retains the upstream features/avgpool/classifier state-dict
layout so the official ImageNet-1K checkpoint loads strictly and produces
identical evaluation logits. LibreYOLO adds its own model factory, checkpoint
metadata, preprocessing, validation, postprocessing, and export integration.

This is torchvision's single-tower "one weird trick" variant, not the
two-GPU 2012 graph. It uses 64 conv1 filters, no local response normalization,
and no grouped convolutions.

The official ImageNet-1K checkpoint is not distributed in the LibreYOLO source
tree. Its separate LibreYOLO Hugging Face mirror uses BSD-3-Clause on an
explicitly disclosed implied basis: the checkpoint is released by the
BSD-licensed project but has no per-object license file. Torchvision warns that
pretrained-model terms may derive from training data and that users remain
responsible for determining permission for their use case. The mirror ships
this BSD text and repeats that caveat; the weight license must not be described
as an explicit checkpoint-specific grant.

BSD 3-Clause License

Copyright (c) Soumith Chintala 2016,

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