LibreYOLO Classification
Collection
Image-classification model families packaged for LibreYOLO (ImageNet-1k, Apache-2.0). MobileNetV4-conv and ConvNeXt V1. • 6 items • Updated
LibreMobileNetV4m-cls
MobileNetV4-conv-Medium image classifier (224px input, ImageNet-1k, 1000 classes), repackaged for LibreYOLO. ~9.7M parameters.
Source
Derived from huggingface/pytorch-image-models (timm),
model mobilenetv4_conv_medium.e500_r224_in1k. Architecture and pretrained weights by Ross Wightman and the timm
contributors (ImageNet-1k, trained in timm; no distillation, no extra data).
Copyright (c) Ross Wightman. Licensed under the Apache License 2.0.
MobileNetV4 paper: "MobileNetV4 - Universal Models for the Mobile Ecosystem" (https://arxiv.org/abs/2404.10518).
Modifications
Learned parameters are unchanged from timm. The checkpoint is metadata-wrapped into the
LibreYOLO format (model_family / task / nc / names). LibreYOLO's native MobileNetV4
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_mobilenetv4_weights.py in the
LibreYOLO source repository.
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreMobileNetV4m-cls.pt")
result = model.predict("image.jpg")[0]
print(result.probs.top1, result.probs.top5)
License
Apache License 2.0. See the LICENSE and NOTICE files in this repository.