Add LiteRT converted convnext_atto

README.md

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+---
+library_name: litert
+base_model: timm/convnext_atto.d2_in1k
+tags:
+  - vision
+  - image-classification
+datasets:
+  - imagenet-1k
+---
+# convnext_atto
+
+Converted TIMM image classification model for LiteRT.
+
+- Source architecture: `convnext_atto`
+- Source checkpoint: `timm/convnext_atto.d2_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): 3.7
+  - GMACs: 0.6
+  - Activations (M): 3.8
+  - Image size: train = 224 x 224, test = 288 x 288
+- **Papers:**
+  - A ConvNet for the 2020s: https://arxiv.org/abs/2201.03545
+- **Original:** https://github.com/huggingface/pytorch-image-models
+- **Dataset:** ImageNet-1k
+
+## Citation
+
+```bibtex
+@misc{rw2019timm,
+  author = {Ross Wightman},
+  title = {PyTorch Image Models},
+  year = {2019},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  doi = {10.5281/zenodo.4414861},
+  howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
+}
+```
+```bibtex
+@article{liu2022convnet,
+  author  = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
+  title   = {A ConvNet for the 2020s},
+  journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year    = {2022},
+}
+```
+

model.tflite

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5945c220d0aaddcd398e716ead094917cd459aa9e50e5ab87ef87cb33e3b10fc
+size 14825808