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 'maxvit_base_tf_384.in21k_ft_in1k', on 2025-01-21 13:00:51 JST
Browse files
README.md
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# Models
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## Beit
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## MaxxVit
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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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| [maxvit_small_tf_512.in1k](https://huggingface.co/timm/maxvit_small_tf_512.in1k) | 68.7M | 58.9G | 512 | True | 768 | 1000 | imagenet-1k | MaxxVit | maxvit_small_tf_512 | 2022-12-03 |
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| [coatnet_rmlp_2_rw_384.sw_in12k_ft_in1k](https://huggingface.co/timm/coatnet_rmlp_2_rw_384.sw_in12k_ft_in1k) | 73.8M | 42.8G | 384 | True | 1024 | 1000 | imagenet-1k | MaxxVit | coatnet_rmlp_2_rw_384 | 2023-01-21 |
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| [maxvit_small_tf_384.in1k](https://huggingface.co/timm/maxvit_small_tf_384.in1k) | 68.7M | 33.1G | 384 | True | 768 | 1000 | imagenet-1k | MaxxVit | maxvit_small_tf_384 | 2022-12-03 |
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# Models
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1014 models exported from TIMM in total.
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## Beit
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## MaxxVit
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31 models with model class `MaxxVit`.
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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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| [maxvit_base_tf_384.in21k_ft_in1k](https://huggingface.co/timm/maxvit_base_tf_384.in21k_ft_in1k) | 119.1M | 68.6G | 384 | True | 768 | 1000 | imagenet-1k | MaxxVit | maxvit_base_tf_384 | 2022-12-03 |
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| [maxvit_small_tf_512.in1k](https://huggingface.co/timm/maxvit_small_tf_512.in1k) | 68.7M | 58.9G | 512 | True | 768 | 1000 | imagenet-1k | MaxxVit | maxvit_small_tf_512 | 2022-12-03 |
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| [coatnet_rmlp_2_rw_384.sw_in12k_ft_in1k](https://huggingface.co/timm/coatnet_rmlp_2_rw_384.sw_in12k_ft_in1k) | 73.8M | 42.8G | 384 | True | 1024 | 1000 | imagenet-1k | MaxxVit | coatnet_rmlp_2_rw_384 | 2023-01-21 |
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| [maxvit_small_tf_384.in1k](https://huggingface.co/timm/maxvit_small_tf_384.in1k) | 68.7M | 33.1G | 384 | True | 768 | 1000 | imagenet-1k | MaxxVit | maxvit_small_tf_384 | 2022-12-03 |
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maxvit_base_tf_384.in21k_ft_in1k/meta.json
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size 169828
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maxvit_base_tf_384.in21k_ft_in1k/model.onnx
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maxvit_base_tf_384.in21k_ft_in1k/preprocess.json
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models.parquet
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size 56247
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