---
license: apache-2.0
library_name: libreyolo
pipeline_tag: image-classification
tags:
- image-classification
- resnet
- imagenet
- libreyolo
datasets:
- imagenet-1k
---

# LibreResNet50-cls

ResNet-50 image classifier (224px, ImageNet-1k, 1000 classes), repackaged for
[LibreYOLO](https://github.com/LibreYOLO/libreyolo). ~25.6M parameters.

## Source

Derived from [huggingface/pytorch-image-models (timm)](https://github.com/huggingface/pytorch-image-models),
model `resnet50.a1_in1k` (the "ResNet Strikes Back" A1 recipe, ImageNet-1k).
Architecture: He et al. 2015 (https://arxiv.org/abs/1512.03385). Weights by Ross
Wightman and the timm contributors. Copyright (c) Ross Wightman. Licensed under the
Apache License 2.0.

## Modifications

Learned parameters are unchanged from timm. The checkpoint is metadata-wrapped into
the LibreYOLO format (model_family / task / nc / names). LibreYOLO's native ResNet
(v1.5) mirrors timm/torchvision module names, so inference is bit-identical to timm
(max_abs_diff == 0, verified by the parity test). See
`weights/convert_resnet_weights.py` in the
[LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo).

## Usage

```python
from libreyolo import LibreYOLO

model = LibreYOLO("LibreResNet50-cls.pt")
result = model.predict("image.jpg")[0]
print(result.probs.top1, result.probs.top5)
```

## License

Apache License 2.0. See the [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE) files in this repository.