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 'mobilenetv4_conv_aa_large.e230_r384_in12k', on 2025-01-19 18:40:10 UTC
Browse files
README.md
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- timm/maxxvitv2_nano_rw_256.sw_in1k
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- timm/mobilenet_edgetpu_v2_m.ra4_e3600_r224_in1k
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- timm/mobilenetv2_100.ra_in1k
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- timm/mobilenetv4_conv_large.e600_r384_in1k
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- timm/mobilenetv4_conv_small.e3600_r256_in1k
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- timm/mobilenetv4_hybrid_medium.ix_e550_r256_in1k
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# Models
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## ByobNet
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## MobileNetV3
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| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset
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## Nest
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- timm/maxxvitv2_nano_rw_256.sw_in1k
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- timm/mobilenet_edgetpu_v2_m.ra4_e3600_r224_in1k
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- timm/mobilenetv2_100.ra_in1k
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- timm/mobilenetv4_conv_aa_large.e230_r384_in12k
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- timm/mobilenetv4_conv_large.e600_r384_in1k
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- timm/mobilenetv4_conv_small.e3600_r256_in1k
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# Models
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92 models exported from TIMM in total.
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## ByobNet
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## MobileNetV3
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7 models with model class `MobileNetV3`.
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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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| [mobilenetv4_conv_aa_large.e230_r384_in12k](https://huggingface.co/timm/mobilenetv4_conv_aa_large.e230_r384_in12k) | 31.2M | 7.0G | 384 | True | 1280 | 11821 | imagenet-12k | MobileNetV3 | mobilenetv4_conv_aa_large | 2024-07-25 |
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| [mobilenetv4_conv_large.e600_r384_in1k](https://huggingface.co/timm/mobilenetv4_conv_large.e600_r384_in1k) | 31.2M | 6.4G | 384 | True | 1280 | 1000 | imagenet-1k | MobileNetV3 | mobilenetv4_conv_large | 2024-06-13 |
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| [mobilenetv4_hybrid_medium.ix_e550_r256_in1k](https://huggingface.co/timm/mobilenetv4_hybrid_medium.ix_e550_r256_in1k) | 9.7M | 1.2G | 256 | True | 1280 | 1000 | imagenet-1k | MobileNetV3 | mobilenetv4_hybrid_medium | 2024-06-24 |
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| [fbnetv3_b.ra2_in1k](https://huggingface.co/timm/fbnetv3_b.ra2_in1k) | 6.6M | 405.6M | 224 | True | 1984 | 1000 | imagenet-1k | MobileNetV3 | fbnetv3_b | 2022-12-16 |
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| [hardcorenas_f.miil_green_in1k](https://huggingface.co/timm/hardcorenas_f.miil_green_in1k) | 6.9M | 340.7M | 224 | True | 1280 | 1000 | imagenet-1k | MobileNetV3 | hardcorenas_f | 2023-04-21 |
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| [mobilenetv4_conv_small.e3600_r256_in1k](https://huggingface.co/timm/mobilenetv4_conv_small.e3600_r256_in1k) | 2.5M | 241.0M | 256 | True | 1280 | 1000 | imagenet-1k | MobileNetV3 | mobilenetv4_conv_small | 2024-12-03 |
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| [hardcorenas_a.miil_green_in1k](https://huggingface.co/timm/hardcorenas_a.miil_green_in1k) | 4.0M | 223.0M | 224 | True | 1280 | 1000 | imagenet-1k | MobileNetV3 | hardcorenas_a | 2023-04-21 |
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## Nest
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mobilenetv4_conv_aa_large.e230_r384_in12k/meta.json
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size 2015422
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mobilenetv4_conv_aa_large.e230_r384_in12k/model.onnx
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mobilenetv4_conv_aa_large.e230_r384_in12k/preprocess.json
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models.parquet
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