LibreYOLO Classification
Collection
Image-classification model families packaged for LibreYOLO (ImageNet-1k, Apache-2.0). MobileNetV4-conv and ConvNeXt V1. • 6 items • Updated
LibreConvNeXts-cls
ConvNeXt-Small image classifier (224px input, ImageNet-1k, 1000 classes), repackaged for LibreYOLO. ~50.2M parameters.
Source
Derived from huggingface/pytorch-image-models (timm),
model convnext_small.fb_in1k. The ConvNeXt architecture is by Zhuang Liu et al. (Meta Platforms),
originally released at facebookresearch/ConvNeXt
under the MIT License. The ImageNet-1k pretrained weights are redistributed by timm under the
Apache License 2.0 (no distillation, no extra data).
Copyright (c) Meta Platforms, Inc. and the timm contributors.
ConvNeXt paper: A ConvNet for the 2020s (https://arxiv.org/abs/2201.03545).
Modifications
Learned parameters are unchanged from timm. The checkpoint is metadata-wrapped into the
LibreYOLO format (model_family / task / nc / names). LibreYOLO's native ConvNeXt
implementation mirrors timm's module names, so inference is bit-identical to timm
(max_abs_diff == 0, verified by the parity test). See
weights/convert_convnext_weights.py in the
LibreYOLO source repository.
Usage
from libreyolo import LibreYOLO
# Auto-downloads from this repo on first use.
model = LibreYOLO("LibreConvNeXts-cls.pt")
result = model.predict("image.jpg")[0]
print(result.probs.top1, result.probs.top5) # ImageNet-1k class id + top-5 ids
License
Apache License 2.0. See the LICENSE and NOTICE files in this repository.
Only ConvNeXt V1 is published here. ConvNeXt-V2's small checkpoints are CC-BY-NC and are not redistributed.