Add model
Browse files- README.md +37 -0
- config.json +41 -0
- pytorch_model.bin +3 -0
README.md
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---
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tags:
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- image-classification
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- timm
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library_tag: timm
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license: apache-2.0
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---
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# Model card for convnext_tiny.in12k_ft_in1k
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A ConvNeXt image classification model. Pretrained on ImageNet-12k (a 11821 class subset of full ImageNet-22k) and fine-tuned on ImageNet-1k by Ross Wightman.
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ImageNet-12k training done on TPUs thanks to support of the [TRC](https://sites.research.google/trc/about/) program.
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Fine-tuning performed on 8x GPU [Lambda Labs](https://lambdalabs.com/) cloud instances.
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## Model Details
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- **Model Type:** Image classification / feature backbone
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## Citation
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```
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@misc{rw2019timm,
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author = {Ross Wightman},
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title = {PyTorch Image Models},
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year = {2019},
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publisher = {GitHub},
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journal = {GitHub repository},
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doi = {10.5281/zenodo.4414861},
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howpublished = {\url{https://github.com/rwightman/pytorch-image-models}}
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}
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```
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```
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@article{liu2022convnet,
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author = {Zhuang Liu and Hanzi Mao and Chao-Yuan Wu and Christoph Feichtenhofer and Trevor Darrell and Saining Xie},
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title = {A ConvNet for the 2020s},
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journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
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year = {2022},
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}
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```
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config.json
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{
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"architecture": "convnext_tiny",
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"num_classes": 1000,
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"num_features": 768,
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"pretrained_cfg": {
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"tag": "in12k_ft_in1k",
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"custom_load": false,
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"input_size": [
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3,
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224,
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224
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],
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"test_input_size": [
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3,
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288,
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288
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],
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"fixed_input_size": false,
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"interpolation": "bicubic",
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"crop_pct": 0.95,
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"test_crop_pct": 1.0,
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"crop_mode": "center",
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"mean": [
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0.485,
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0.456,
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0.406
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],
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"std": [
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0.229,
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0.224,
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0.225
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],
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"num_classes": 1000,
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"pool_size": [
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7,
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7
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],
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"first_conv": "stem.0",
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"classifier": "head.fc"
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}
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1abc6ff66688819cab2f7f8b1d9e14f7830c947ad663bd3c1f6681c0d31fcce6
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size 114420885
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