resnet-50
ResNet model pre-trained on ImageNet-1k at resolution 224x224. It was introduced in the paper Deep Residual Learning for Image Recognition by He et al.
Params
30 M
Context
—
Downloads 30d
577 K
Likes
510
Download history
daily snapshots · 55 days
▲ 1.2 M in the last 30 days (67.7%)
1.8 M577 K
Aug 22Sep 1Sep 11Sep 20
1.8 M577 K
Jul 28Aug 15Sep 2Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.1 GB | 0.6 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- ResNetForImageClassification
- Parameters
- 30 M
- Tensor type
- F32
- Licence
- apache-2.0
- First seen on the Hub
- 2022-03-16
- Training datasets
- imagenet-1k
- Added to our catalog
- 2026-07-28
Compare with any image-classification model