timm / image-classification Open weights updated 1 year ago

vit_base_patch16_384.augreg_in21k_ft_in1k

Name: vit_base_patch16_384.augreg_in21k_ft_in1k
Author: timm

A Vision Transformer (ViT) image classification model. Trained on ImageNet-21k and fine-tuned on ImageNet-1k (with additional augmentation and regularization) in JAX by paper authors, ported to PyTorch by Ross Wightman.

Params

90 M

Context

—

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192 K

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Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

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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	0.3 GB	0.9 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: 90 M
Tensor type: F32
Licence: apache-2.0
First seen on the Hub: 2022-12-22
Training datasets: imagenet-1k, imagenet-21k
Added to our catalog: 2026-09-02

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