| --- |
| 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]). |
|
|
