timm / image-classification Open weights updated 1 year ago

tf_efficientnetv2_s.in21k_ft_in1k

A EfficientNet-v2 image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k in Tensorflow by paper authors, ported to PyTorch by Ross Wightman.

Params
20 M
Context
—
Downloads 30d
3.6 M
Likes
16
Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 106 days
▲ 2.0 M in the last 30 days (122.6%)
3.6 M1.4 M
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.

FileQuantSizeEst. VRAMVerdict 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

Parameters
20 M
Tensor type
F32
Licence
apache-2.0
First seen on the Hub
2022-12-13
Training datasets
imagenet-1k, imagenet-21k
Added to our catalog
2026-07-28
Compare with any image-classification model