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 'senet154.gluon_in1k', on 2025-01-21 12:50:55 JST
Browse files- README.md +3 -2
- models.parquet +2 -2
- senet154.gluon_in1k/meta.json +3 -0
- senet154.gluon_in1k/model.onnx +3 -0
- senet154.gluon_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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|:---------------------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:-------------|:--------|:----------------------|:-------------|
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| [resnest200e.in1k](https://huggingface.co/timm/resnest200e.in1k) | 70.2M | 35.9G | 320 | True | 2048 | 1000 | imagenet-1k | ResNet | resnest200e | 2023-04-24 |
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| [seresnextaa101d_32x8d.sw_in12k_ft_in1k_288](https://huggingface.co/timm/seresnextaa101d_32x8d.sw_in12k_ft_in1k_288) | 93.6M | 28.6G | 288 | True | 2048 | 1000 | imagenet-1k | ResNet | seresnextaa101d_32x8d | 2023-04-06 |
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| [resnetrs200.tf_in1k](https://huggingface.co/timm/resnetrs200.tf_in1k) | 93.2M | 20.3G | 256 | True | 2048 | 1000 | imagenet-1k | ResNet | resnetrs200 | 2023-04-06 |
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| [resnet200d.ra2_in1k](https://huggingface.co/timm/resnet200d.ra2_in1k) | 64.7M | 20.1G | 256 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet200d | 2023-04-06 |
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| [seresnextaa101d_32x8d.sw_in12k_ft_in1k](https://huggingface.co/timm/seresnextaa101d_32x8d.sw_in12k_ft_in1k) | 93.6M | 17.3G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | seresnextaa101d_32x8d | 2023-04-06 |
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# Models
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1010 models exported from TIMM in total.
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## Beit
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## ResNet
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155 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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| [resnest200e.in1k](https://huggingface.co/timm/resnest200e.in1k) | 70.2M | 35.9G | 320 | True | 2048 | 1000 | imagenet-1k | ResNet | resnest200e | 2023-04-24 |
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| [seresnextaa101d_32x8d.sw_in12k_ft_in1k_288](https://huggingface.co/timm/seresnextaa101d_32x8d.sw_in12k_ft_in1k_288) | 93.6M | 28.6G | 288 | True | 2048 | 1000 | imagenet-1k | ResNet | seresnextaa101d_32x8d | 2023-04-06 |
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| [senet154.gluon_in1k](https://huggingface.co/timm/senet154.gluon_in1k) | 115.1M | 20.8G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | senet154 | 2023-04-06 |
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| [resnetrs200.tf_in1k](https://huggingface.co/timm/resnetrs200.tf_in1k) | 93.2M | 20.3G | 256 | True | 2048 | 1000 | imagenet-1k | ResNet | resnetrs200 | 2023-04-06 |
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| [resnet200d.ra2_in1k](https://huggingface.co/timm/resnet200d.ra2_in1k) | 64.7M | 20.1G | 256 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet200d | 2023-04-06 |
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| [seresnextaa101d_32x8d.sw_in12k_ft_in1k](https://huggingface.co/timm/seresnextaa101d_32x8d.sw_in12k_ft_in1k) | 93.6M | 17.3G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | seresnextaa101d_32x8d | 2023-04-06 |
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models.parquet
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senet154.gluon_in1k/meta.json
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senet154.gluon_in1k/model.onnx
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senet154.gluon_in1k/preprocess.json
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size 734
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