edgenext_small.usi_in1k
An EdgeNeXt image classification model. Trained on ImageNet-1k by paper authors using distillation (USI as per Solving ImageNet).
Params
10 M
Context
—
Downloads 30d
271 K
Likes
6
Download history
daily snapshots · 106 days
▲ 76 K in the last 30 days (39.0%)
276 K195 K
Oct 12Oct 22Nov 1Nov 10
291 K185 K
Aug 13Sep 12Oct 12Nov 10
343 K185 K
Jul 28Sep 1Oct 6Nov 10
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 | 0.0 GB | 0.5 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Parameters
- 10 M
- Tensor type
- F32
- Licence
- mit
- First seen on the Hub
- 2023-04-23
- Training datasets
- imagenet-1k
- Added to our catalog
- 2026-07-28
Compare with any image-classification model