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---
pipeline_tag: image-classification
base_model:
- timm/convformer_m36.sail_in22k_ft_in1k
- timm/convformer_s36.sail_in1k_384
- timm/convmixer_1024_20_ks9_p14.in1k
- timm/convnext_nano.r384_in12k_ft_in1k
- timm/convnext_pico.d1_in1k
- timm/convnextv2_atto.fcmae_ft_in1k
- timm/ecaresnet50t.a1_in1k
- timm/efficientnet_b5.sw_in12k
- timm/efficientvit_b1.r256_in1k
- timm/efficientvit_b2.r256_in1k
- timm/efficientvit_l1.r224_in1k
- timm/fbnetv3_b.ra2_in1k
- timm/ghostnetv2_100.in1k
- timm/hardcorenas_f.miil_green_in1k
- timm/hgnetv2_b3.ssld_stage1_in22k_in1k
- timm/hgnetv2_b4.ssld_stage2_ft_in1k
- timm/inception_resnet_v2.tf_in1k
- timm/mobilenetv2_100.ra_in1k
- timm/mobilevitv2_050.cvnets_in1k
- timm/nextvit_base.bd_in1k
- timm/regnetx_080.tv2_in1k
- timm/repghostnet_050.in1k
- timm/repvgg_b1.rvgg_in1k
- timm/resnetaa50.a1h_in1k
- timm/resnetv2_101x1_bit.goog_in21k_ft_in1k
- timm/rexnetr_300.sw_in12k_ft_in1k
- timm/swin_base_patch4_window7_224.ms_in1k
- timm/vit_base_patch16_clip_384.laion2b_ft_in12k_in1k
- timm/vit_base_r50_s16_384.orig_in21k_ft_in1k
- timm/vit_little_patch16_reg4_gap_256.sbb_in1k
- timm/xcit_small_24_p16_224.fb_in1k
language:
- en
tags:
- timm
- image
- dghs-realutils
library_name: dghs-imgutils
---
ONNX export version from [TIMM](https://huggingface.co/timm).
# Models
31 models exported from TIMM in total.
## ByobNet
2 models with model class `ByobNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:----------------|:-------------|
| [repvgg_b1.rvgg_in1k](https://huggingface.co/timm/repvgg_b1.rvgg_in1k) | 57.3M | 13.1G | 224 | True | 2048 | 1000 | imagenet-1k | ByobNet | repvgg_b1 | 2023-03-22 |
| [mobilevitv2_050.cvnets_in1k](https://huggingface.co/timm/mobilevitv2_050.cvnets_in1k) | 1.4M | 464.6M | 256 | True | 256 | 1000 | imagenet-1k | ByobNet | mobilevitv2_050 | 2023-04-24 |
## ConvMixer
1 model with model class `ConvMixer`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:----------|:--------------------------|:-------------|
| [convmixer_1024_20_ks9_p14.in1k](https://huggingface.co/timm/convmixer_1024_20_ks9_p14.in1k) | 24.4M | 6.0G | 224 | True | 1024 | 1000 | imagenet-1k | ConvMixer | convmixer_1024_20_ks9_p14 | 2023-04-24 |
## ConvNeXt
3 models with model class `ConvNeXt`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------|:----------------|:-------------|
| [convnext_nano.r384_in12k_ft_in1k](https://huggingface.co/timm/convnext_nano.r384_in12k_ft_in1k) | 15.6M | 7.2G | 384 | True | 640 | 1000 | imagenet-1k | ConvNeXt | convnext_nano | 2024-12-31 |
| [convnext_pico.d1_in1k](https://huggingface.co/timm/convnext_pico.d1_in1k) | 9.0M | 1.4G | 224 | True | 512 | 1000 | imagenet-1k | ConvNeXt | convnext_pico | 2022-12-13 |
| [convnextv2_atto.fcmae_ft_in1k](https://huggingface.co/timm/convnextv2_atto.fcmae_ft_in1k) | 3.7M | 547.3M | 224 | True | 320 | 1000 | imagenet-1k | ConvNeXt | convnextv2_atto | 2023-01-05 |
## EfficientNet
2 models with model class `EfficientNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:-------------|:-------------|:----------------|:-------------|
| [efficientnet_b5.sw_in12k](https://huggingface.co/timm/efficientnet_b5.sw_in12k) | 52.4M | 8.1G | 416 | True | 2048 | 11821 | imagenet-12k | EfficientNet | efficientnet_b5 | 2022-12-12 |
| [mobilenetv2_100.ra_in1k](https://huggingface.co/timm/mobilenetv2_100.ra_in1k) | 3.5M | 300.8M | 224 | True | 1280 | 1000 | imagenet-1k | EfficientNet | mobilenetv2_100 | 2022-12-13 |
## EfficientVit
2 models with model class `EfficientVit`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-----------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:-------------|:----------------|:-------------|
| [efficientvit_b2.r256_in1k](https://huggingface.co/timm/efficientvit_b2.r256_in1k) | 24.3M | 2.1G | 256 | True | 2560 | 1000 | imagenet-1k | EfficientVit | efficientvit_b2 | 2023-08-18 |
| [efficientvit_b1.r256_in1k](https://huggingface.co/timm/efficientvit_b1.r256_in1k) | 9.1M | 689.0M | 256 | True | 1600 | 1000 | imagenet-1k | EfficientVit | efficientvit_b1 | 2023-08-18 |
## EfficientVitLarge
1 model with model class `EfficientVitLarge`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-----------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------------|:----------------|:-------------|
| [efficientvit_l1.r224_in1k](https://huggingface.co/timm/efficientvit_l1.r224_in1k) | 52.7M | 5.3G | 224 | True | 3200 | 1000 | imagenet-1k | EfficientVitLarge | efficientvit_l1 | 2023-11-21 |
## GhostNet
1 model with model class `GhostNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-----------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------|:---------------|:-------------|
| [ghostnetv2_100.in1k](https://huggingface.co/timm/ghostnetv2_100.in1k) | 4.9M | 183.8M | 224 | True | 1280 | 1000 | imagenet-1k | GhostNet | ghostnetv2_100 | 2023-08-20 |
## HighPerfGpuNet
2 models with model class `HighPerfGpuNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------------|:---------------|:-------------|
| [hgnetv2_b4.ssld_stage2_ft_in1k](https://huggingface.co/timm/hgnetv2_b4.ssld_stage2_ft_in1k) | 19.8M | 2.8G | 224 | True | 2048 | 1000 | imagenet-1k | HighPerfGpuNet | hgnetv2_b4 | 2024-02-12 |
| [hgnetv2_b3.ssld_stage1_in22k_in1k](https://huggingface.co/timm/hgnetv2_b3.ssld_stage1_in22k_in1k) | 16.3M | 1.8G | 224 | True | 2048 | 1000 | imagenet-1k | HighPerfGpuNet | hgnetv2_b3 | 2024-02-12 |
## InceptionResnetV2
1 model with model class `InceptionResnetV2`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------------|:--------------------|:-------------|
| [inception_resnet_v2.tf_in1k](https://huggingface.co/timm/inception_resnet_v2.tf_in1k) | 55.8M | 13.2G | 299 | True | 1536 | 1000 | imagenet-1k | InceptionResnetV2 | inception_resnet_v2 | 2023-04-25 |
## MetaFormer
2 models with model class `MetaFormer`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:-----------|:---------------|:-------------|
| [convformer_s36.sail_in1k_384](https://huggingface.co/timm/convformer_s36.sail_in1k_384) | 40.0M | 22.4G | 384 | True | 512 | 1000 | imagenet-1k | MetaFormer | convformer_s36 | 2023-05-05 |
| [convformer_m36.sail_in22k_ft_in1k](https://huggingface.co/timm/convformer_m36.sail_in22k_ft_in1k) | 57.0M | 12.8G | 224 | True | 576 | 1000 | imagenet-1k | MetaFormer | convformer_m36 | 2023-05-05 |
## MobileNetV3
2 models with model class `MobileNetV3`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------|:---------------|:-------------|
| [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 |
| [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 |
## NextViT
1 model with model class `NextViT`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [nextvit_base.bd_in1k](https://huggingface.co/timm/nextvit_base.bd_in1k) | 44.8M | 8.3G | 224 | True | 1024 | 1000 | imagenet-1k | NextViT | nextvit_base | 2024-02-11 |
## RegNet
1 model with model class `RegNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [regnetx_080.tv2_in1k](https://huggingface.co/timm/regnetx_080.tv2_in1k) | 39.5M | 8.0G | 224 | True | 1920 | 1000 | imagenet-1k | RegNet | regnetx_080 | 2023-03-21 |
## RepGhostNet
1 model with model class `RepGhostNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------|:----------------|:-------------|
| [repghostnet_050.in1k](https://huggingface.co/timm/repghostnet_050.in1k) | 1.0M | 53.4M | 224 | True | 1280 | 1000 | imagenet-1k | RepGhostNet | repghostnet_050 | 2023-08-19 |
## ResNet
2 models with model class `ResNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [resnetaa50.a1h_in1k](https://huggingface.co/timm/resnetaa50.a1h_in1k) | 25.6M | 5.2G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnetaa50 | 2023-04-05 |
| [ecaresnet50t.a1_in1k](https://huggingface.co/timm/ecaresnet50t.a1_in1k) | 25.6M | 4.3G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | ecaresnet50t | 2023-04-05 |
## ResNetV2
1 model with model class `ResNetV2`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-----------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:---------|:-------------------|:-------------|
| [resnetv2_101x1_bit.goog_in21k_ft_in1k](https://huggingface.co/timm/resnetv2_101x1_bit.goog_in21k_ft_in1k) | 2.0M | 2.5M | 448 | True | 2048 | 1000 | imagenet-1k | ResNetV2 | resnetv2_101x1_bit | 2023-03-22 |
## RexNet
1 model with model class `RexNet`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-----------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:---------------|:-------------|
| [rexnetr_300.sw_in12k_ft_in1k](https://huggingface.co/timm/rexnetr_300.sw_in12k_ft_in1k) | 34.7M | 3.3G | 224 | True | 3840 | 1000 | imagenet-1k | RexNet | rexnetr_300 | 2023-03-20 |
## SwinTransformer
1 model with model class `SwinTransformer`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:---------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:----------------|:-----------------------------|:-------------|
| [swin_base_patch4_window7_224.ms_in1k](https://huggingface.co/timm/swin_base_patch4_window7_224.ms_in1k) | 87.7M | 15.2G | 224 | True | 1024 | 1000 | imagenet-1k | SwinTransformer | swin_base_patch4_window7_224 | 2023-03-18 |
## VisionTransformer
3 models with model class `VisionTransformer`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:------------------|:--------------------------------|:-------------|
| [vit_base_r50_s16_384.orig_in21k_ft_in1k](https://huggingface.co/timm/vit_base_r50_s16_384.orig_in21k_ft_in1k) | 86.6M | 49.5G | 384 | True | 768 | 1000 | imagenet-1k | VisionTransformer | vit_base_r50_s16_384 | 2022-12-23 |
| [vit_base_patch16_clip_384.laion2b_ft_in12k_in1k](https://huggingface.co/timm/vit_base_patch16_clip_384.laion2b_ft_in12k_in1k) | 86.4M | 49.4G | 384 | True | 768 | 1000 | imagenet-1k | VisionTransformer | vit_base_patch16_clip_384 | 2022-11-11 |
| [vit_little_patch16_reg4_gap_256.sbb_in1k](https://huggingface.co/timm/vit_little_patch16_reg4_gap_256.sbb_in1k) | 22.4M | 5.7G | 256 | True | 320 | 1000 | imagenet-1k | VisionTransformer | vit_little_patch16_reg4_gap_256 | 2024-05-10 |
## Xcit
1 model with model class `Xcit`.
| Name | Params | Flops | Input Size | Can Classify | Features | Classes | Dataset | Model | Architecture | Created At |
|:-------------------------------------------------------------------------------------------|:---------|:--------|-------------:|:---------------|-----------:|----------:|:------------|:--------|:----------------------|:-------------|
| [xcit_small_24_p16_224.fb_in1k](https://huggingface.co/timm/xcit_small_24_p16_224.fb_in1k) | 47.6M | 8.9G | 224 | True | 384 | 1000 | imagenet-1k | Xcit | xcit_small_24_p16_224 | 2023-04-13 |
|