Instructions to use deepghs/timms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use deepghs/timms with timm:
import timm model = timm.create_model("hf_hub:deepghs/timms", pretrained=True) - Notebooks
- Google Colab
- Kaggle
narugo1992 commited on
Export model 'resnet26d.bt_in1k', on 2025-01-20 05:31:28 UTC
Browse files- README.md +3 -2
- models.parquet +2 -2
- resnet26d.bt_in1k/meta.json +3 -0
- resnet26d.bt_in1k/model.onnx +3 -0
- resnet26d.bt_in1k/preprocess.json +3 -0
README.md
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# Models
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## Beit
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## ResNet
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| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
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| [resnet50_gn.a1h_in1k](https://huggingface.co/timm/resnet50_gn.a1h_in1k) | 25.5M | 4.1G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet50_gn | 2023-04-05 |
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| [resnet101.a3_in1k](https://huggingface.co/timm/resnet101.a3_in1k) | 44.5M | 4.0G | 160 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet101 | 2023-04-05 |
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| [resnest14d.gluon_in1k](https://huggingface.co/timm/resnest14d.gluon_in1k) | 10.6M | 2.8G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnest14d | 2023-04-23 |
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| [resnet18d.ra2_in1k](https://huggingface.co/timm/resnet18d.ra2_in1k) | 11.7M | 2.1G | 224 | True | 512 | 1000 | imagenet-1k | ResNet | resnet18d | 2023-04-05 |
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| [resnet34.a3_in1k](https://huggingface.co/timm/resnet34.a3_in1k) | 21.8M | 1.9G | 160 | True | 512 | 1000 | imagenet-1k | ResNet | resnet34 | 2023-04-05 |
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| [resnet18.tv_in1k](https://huggingface.co/timm/resnet18.tv_in1k) | 11.7M | 1.8G | 224 | True | 512 | 1000 | imagenet-1k | ResNet | resnet18 | 2023-04-05 |
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# Models
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267 models exported from TIMM in total.
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## Beit
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## ResNet
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46 models with model class `ResNet`.
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| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
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|:-----------------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:-------------|:--------|:------------------|:-------------|
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| [resnet50_gn.a1h_in1k](https://huggingface.co/timm/resnet50_gn.a1h_in1k) | 25.5M | 4.1G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet50_gn | 2023-04-05 |
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| [resnet101.a3_in1k](https://huggingface.co/timm/resnet101.a3_in1k) | 44.5M | 4.0G | 160 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet101 | 2023-04-05 |
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| [resnest14d.gluon_in1k](https://huggingface.co/timm/resnest14d.gluon_in1k) | 10.6M | 2.8G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnest14d | 2023-04-23 |
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| [resnet26d.bt_in1k](https://huggingface.co/timm/resnet26d.bt_in1k) | 16.0M | 2.6G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet26d | 2023-04-05 |
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| [resnet18d.ra2_in1k](https://huggingface.co/timm/resnet18d.ra2_in1k) | 11.7M | 2.1G | 224 | True | 512 | 1000 | imagenet-1k | ResNet | resnet18d | 2023-04-05 |
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| [resnet34.a3_in1k](https://huggingface.co/timm/resnet34.a3_in1k) | 21.8M | 1.9G | 160 | True | 512 | 1000 | imagenet-1k | ResNet | resnet34 | 2023-04-05 |
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| [resnet18.tv_in1k](https://huggingface.co/timm/resnet18.tv_in1k) | 11.7M | 1.8G | 224 | True | 512 | 1000 | imagenet-1k | ResNet | resnet18 | 2023-04-05 |
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models.parquet
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resnet26d.bt_in1k/meta.json
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resnet26d.bt_in1k/model.onnx
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resnet26d.bt_in1k/preprocess.json
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size 734
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