Add LiteRT converted repvit_m0_9

README.md

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+---
+library_name: litert
+base_model: timm/repvit_m0_9.dist_300e_in1k
+tags:
+  - vision
+  - image-classification
+datasets:
+  - imagenet-1k
+---
+# repvit_m0_9
+
+Converted TIMM image classification model for LiteRT.
+
+- Source architecture: `repvit_m0_9`
+- Source checkpoint: `timm/repvit_m0_9.dist_300e_in1k`
+- File: `model.tflite`
+- Input: `float32` tensor in NCHW layout, shape `[1, 3, 224, 224]`
+- Output: ImageNet-1K logits, shape `[1, 1000]`
+
+## Model Details
+
+- **Model Type:** Image classification / feature backbone
+- **Model Stats:**
+  - Params (M): 5.5
+  - GMACs: 0.8
+  - Activations (M): 7.4
+  - Image size: 224 x 224
+- **Papers:**
+  - RepViT: Revisiting Mobile CNN From ViT Perspective: https://arxiv.org/abs/2307.09283
+- **Original:** https://github.com/THU-MIG/RepViT
+- **Dataset:** ImageNet-1k
+
+## Citation
+
+```bibtex
+@misc{wang2023repvit,
+  title={RepViT: Revisiting Mobile CNN From ViT Perspective}, 
+  author={Ao Wang and Hui Chen and Zijia Lin and Hengjun Pu and Guiguang Ding},
+  year={2023},
+  eprint={2307.09283},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV}
+}
+```
+

model.tflite

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+size 22025632