--- pipeline_tag: image-classification base_model: - timm/caformer_s18.sail_in22k - 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_040.pycls_in1k - timm/regnetx_080.tv2_in1k - timm/repghostnet_050.in1k - timm/repvgg_b1.rvgg_in1k - timm/resnet50d.a1_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 34 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 3 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 | | [caformer_s18.sail_in22k](https://huggingface.co/timm/caformer_s18.sail_in22k) | 69.0M | 3.9G | 224 | True | 512 | 21841 | imagenet-22k | MetaFormer | caformer_s18 | 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 2 models 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 | | [regnetx_040.pycls_in1k](https://huggingface.co/timm/regnetx_040.pycls_in1k) | 22.0M | 4.0G | 224 | True | 1360 | 1000 | imagenet-1k | RegNet | regnetx_040 | 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 3 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 | | [resnet50d.a1_in1k](https://huggingface.co/timm/resnet50d.a1_in1k) | 25.6M | 4.4G | 224 | True | 2048 | 1000 | imagenet-1k | ResNet | resnet50d | 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 |