---
library_name: litert
base_model: timm/pvt_v2_b2.in1k
tags:
  - vision
  - image-classification
datasets:
  - imagenet-1k
---
# pvt_v2_b2

Converted TIMM image classification model for LiteRT.

- Source architecture: `pvt_v2_b2`
- Source checkpoint: `timm/pvt_v2_b2.in1k`
- File: `model.tflite`
- Input: `float32` tensor in NCHW layout, shape `[1, 3, 224, 224]`
- Output: ImageNet-1K logits, shape `[1, 1000]`

## Runtime Status

- CPU smoke test: passed with LiteRT `CompiledModel`.
- GPU delegation: currently blocked for this model by rank-5 tensor patterns in the GPU backend, mostly `RESHAPE`, `TRANSPOSE`, and related window/attention operations. The model is published as CPU-ready while GPU support is being improved.

## Model Details

- **Model Type:** Image classification / feature backbone
- **Model Stats:**
  - Params (M): 25.4
  - GMACs: 4.0
  - Activations (M): 27.5
  - Image size: 224 x 224
- **Papers:**
  - PVT v2: Improved Baselines with Pyramid Vision Transformer: https://arxiv.org/abs/2106.13797
- **Dataset:** ImageNet-1k
- **Original:** https://github.com/whai362/PVT

## Citation

```bibtex
@article{wang2021pvtv2,
  title={Pvtv2: Improved baselines with pyramid vision transformer},
  author={Wang, Wenhai and Xie, Enze and Li, Xiang and Fan, Deng-Ping and Song, Kaitao and Liang, Ding and Lu, Tong and Luo, Ping and Shao, Ling},
  journal={Computational Visual Media},
  volume={8},
  number={3},
  pages={1--10},
  year={2022},
  publisher={Springer}
}
```