---
license: apache-2.0
tags:
  - image-classification
  - vision-transformer
  - microvit
library_name: transformers
---

# MicroViT-S2

ImageNet-1K pretrained MicroViT-S2 (10.0M params, 74.6% Top-1 accuracy).

**Architecture:** SHViT (Single-Head Vision Transformer) backbone.
**Source paper:** https://arxiv.org/abs/2502.05800
**Official repo:** https://github.com/novendrastywn/MicroViT

## Usage

```python
from transformers import AutoModelForImageClassification, AutoImageProcessor

# Load ImageNet pretrained (1000 classes)
model = AutoModelForImageClassification.from_pretrained(
    "henriquequeirozcunha/microvit-s2",
    trust_remote_code=True,
)

# Fine-tune for binary classification
model = AutoModelForImageClassification.from_pretrained(
    "henriquequeirozcunha/microvit-s2",
    num_labels=2,
    ignore_mismatched_sizes=True,
    trust_remote_code=True,
)
```

**Preprocessing:** 224×224, ImageNet normalization
(mean=[0.485,0.456,0.406], std=[0.229,0.224,0.225]).