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custom-resnet50d

Dadigua12581

A Transformers-compatible wrapper around the pretrained `timm/resnet50d.ra2_in1k` ImageNet-1k classifier, following the custom model tutorial. The pretrained weights are copied from timm without additional training. The model has 25,576,264 parameters and predicts 1,000 ImageNet classes. The repository includes the custom Python code, safetensors weights, configuration, ImageNet class names, and image processor. The processor converts images to RGB, resizes the shorter edge to 256 pixels using bicubic interpolation, center-crops to 224 x 224, rescales to [0, 1], and normalizes with ImageNet mean and standard deviation.

Image classification

Input Image→ Output Not verified

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Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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custom-resnet50d

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