🎯 Timm Encoders

🎯 Timm Encoders#

Pytorch Image Models (a.k.a. timm) has a lot of pretrained models and interface which allows using these models as encoders in smp, however, not all models are supported

  • not all transformer models have features_only functionality implemented that is required for encoder

  • some models have inappropriate strides

Below is a table of suitable encoders (for DeepLabV3, DeepLabV3+, and PAN dilation support is needed also)

Total number of encoders: 812 (593+219)

Note

To use following encoders you have to add prefix tu-, e.g. tu-adv_inception_v3

Traditional-Style#

These models typically produce feature maps at the following downsampling scales relative to the input resolution: 1/2, 1/4, 1/8, 1/16, and 1/32

Encoder name

Support dilation

bat_resnext26ts

βœ…

botnet26t_256

βœ…

botnet50ts_256

βœ…

coatnet_0_224

coatnet_0_rw_224

coatnet_1_224

coatnet_1_rw_224

coatnet_2_224

coatnet_2_rw_224

coatnet_3_224

coatnet_3_rw_224

coatnet_4_224

coatnet_5_224

coatnet_bn_0_rw_224

coatnet_nano_cc_224

coatnet_nano_rw_224

coatnet_pico_rw_224

coatnet_rmlp_0_rw_224

coatnet_rmlp_1_rw2_224

coatnet_rmlp_1_rw_224

coatnet_rmlp_2_rw_224

coatnet_rmlp_2_rw_384

coatnet_rmlp_3_rw_224

coatnet_rmlp_nano_rw_224

coatnext_nano_rw_224

cs3darknet_focus_l

βœ…

cs3darknet_focus_m

βœ…

cs3darknet_focus_s

βœ…

cs3darknet_focus_x

βœ…

cs3darknet_l

βœ…

cs3darknet_m

βœ…

cs3darknet_s

βœ…

cs3darknet_x

βœ…

cs3edgenet_x

βœ…

cs3se_edgenet_x

βœ…

cs3sedarknet_l

βœ…

cs3sedarknet_x

βœ…

cs3sedarknet_xdw

βœ…

cspdarknet53

βœ…

cspresnet50

βœ…

cspresnet50d

βœ…

cspresnet50w

βœ…

cspresnext50

βœ…

darknet17

βœ…

darknet21

βœ…

darknet53

βœ…

darknetaa53

βœ…

densenet121

densenet161

densenet169

densenet201

densenet264d

densenetblur121d

dla34

dla46_c

dla46x_c

dla60

dla60_res2net

dla60_res2next

dla60x

dla60x_c

dla102

dla102x

dla102x2

dla169

dm_nfnet_f0

βœ…

dm_nfnet_f1

βœ…

dm_nfnet_f2

βœ…

dm_nfnet_f3

βœ…

dm_nfnet_f4

βœ…

dm_nfnet_f5

βœ…

dm_nfnet_f6

βœ…

dpn48b

dpn68

dpn68b

dpn92

dpn98

dpn107

dpn131

eca_botnext26ts_256

βœ…

eca_halonext26ts

βœ…

eca_nfnet_l0

βœ…

eca_nfnet_l1

βœ…

eca_nfnet_l2

βœ…

eca_nfnet_l3

βœ…

eca_resnet33ts

βœ…

eca_resnext26ts

βœ…

eca_vovnet39b

ecaresnet26t

βœ…

ecaresnet50d

βœ…

ecaresnet50d_pruned

βœ…

ecaresnet50t

βœ…

ecaresnet101d

βœ…

ecaresnet101d_pruned

βœ…

ecaresnet200d

βœ…

ecaresnet269d

βœ…

ecaresnetlight

βœ…

ecaresnext26t_32x4d

βœ…

ecaresnext50t_32x4d

βœ…

efficientnet_b0

βœ…

efficientnet_b0_g8_gn

βœ…

efficientnet_b0_g16_evos

βœ…

efficientnet_b0_gn

βœ…

efficientnet_b1

βœ…

efficientnet_b1_pruned

βœ…

efficientnet_b2

βœ…

efficientnet_b2_pruned

βœ…

efficientnet_b3

βœ…

efficientnet_b3_g8_gn

βœ…

efficientnet_b3_gn

βœ…

efficientnet_b3_pruned

βœ…

efficientnet_b4

βœ…

efficientnet_b5

βœ…

efficientnet_b6

βœ…

efficientnet_b7

βœ…

efficientnet_b8

βœ…

efficientnet_blur_b0

βœ…

efficientnet_cc_b0_4e

βœ…

efficientnet_cc_b0_8e

βœ…

efficientnet_cc_b1_8e

βœ…

efficientnet_el

βœ…

efficientnet_el_pruned

βœ…

efficientnet_em

βœ…

efficientnet_es

βœ…

efficientnet_es_pruned

βœ…

efficientnet_l2

βœ…

efficientnet_lite0

βœ…

efficientnet_lite1

βœ…

efficientnet_lite2

βœ…

efficientnet_lite3

βœ…

efficientnet_lite4

βœ…

efficientnetv2_l

βœ…

efficientnetv2_m

βœ…

efficientnetv2_rw_m

βœ…

efficientnetv2_rw_s

βœ…

efficientnetv2_rw_t

βœ…

efficientnetv2_s

βœ…

efficientnetv2_xl

βœ…

ese_vovnet19b_dw

ese_vovnet19b_slim

ese_vovnet19b_slim_dw

ese_vovnet39b

ese_vovnet39b_evos

ese_vovnet57b

ese_vovnet99b

fbnetc_100

βœ…

fbnetv3_b

βœ…

fbnetv3_d

βœ…

fbnetv3_g

βœ…

gc_efficientnetv2_rw_t

βœ…

gcresnet33ts

βœ…

gcresnet50t

βœ…

gcresnext26ts

βœ…

gcresnext50ts

βœ…

gernet_l

βœ…

gernet_m

βœ…

gernet_s

βœ…

ghostnet_050

ghostnet_100

ghostnet_130

ghostnetv2_100

ghostnetv2_130

ghostnetv2_160

halo2botnet50ts_256

βœ…

halonet26t

βœ…

halonet50ts

βœ…

halonet_h1

βœ…

haloregnetz_b

βœ…

hardcorenas_a

βœ…

hardcorenas_b

βœ…

hardcorenas_c

βœ…

hardcorenas_d

βœ…

hardcorenas_e

βœ…

hardcorenas_f

βœ…

hrnet_w18

hrnet_w18_small

hrnet_w18_small_v2

hrnet_w18_ssld

hrnet_w30

hrnet_w32

hrnet_w40

hrnet_w44

hrnet_w48

hrnet_w48_ssld

hrnet_w64

lambda_resnet26rpt_256

βœ…

lambda_resnet26t

βœ…

lambda_resnet50ts

βœ…

lamhalobotnet50ts_256

βœ…

lcnet_035

βœ…

lcnet_050

βœ…

lcnet_075

βœ…

lcnet_100

βœ…

lcnet_150

βœ…

legacy_senet154

legacy_seresnet18

legacy_seresnet34

legacy_seresnet50

legacy_seresnet101

legacy_seresnet152

legacy_seresnext26_32x4d

legacy_seresnext50_32x4d

legacy_seresnext101_32x4d

maxvit_base_tf_224

maxvit_base_tf_384

maxvit_base_tf_512

maxvit_large_tf_224

maxvit_large_tf_384

maxvit_large_tf_512

maxvit_nano_rw_256

maxvit_pico_rw_256

maxvit_rmlp_base_rw_224

maxvit_rmlp_base_rw_384

maxvit_rmlp_nano_rw_256

maxvit_rmlp_pico_rw_256

maxvit_rmlp_small_rw_224

maxvit_rmlp_small_rw_256

maxvit_rmlp_tiny_rw_256

maxvit_small_tf_224

maxvit_small_tf_384

maxvit_small_tf_512

maxvit_tiny_pm_256

maxvit_tiny_rw_224

maxvit_tiny_rw_256

maxvit_tiny_tf_224

maxvit_tiny_tf_384

maxvit_tiny_tf_512

maxvit_xlarge_tf_224

maxvit_xlarge_tf_384

maxvit_xlarge_tf_512

maxxvit_rmlp_nano_rw_256

maxxvit_rmlp_small_rw_256

maxxvit_rmlp_tiny_rw_256

maxxvitv2_nano_rw_256

maxxvitv2_rmlp_base_rw_224

maxxvitv2_rmlp_base_rw_384

maxxvitv2_rmlp_large_rw_224

mixnet_l

βœ…

mixnet_m

βœ…

mixnet_s

βœ…

mixnet_xl

βœ…

mixnet_xxl

βœ…

mnasnet_050

βœ…

mnasnet_075

βœ…

mnasnet_100

βœ…

mnasnet_140

βœ…

mnasnet_small

βœ…

mobilenet_edgetpu_100

βœ…

mobilenet_edgetpu_v2_l

βœ…

mobilenet_edgetpu_v2_m

βœ…

mobilenet_edgetpu_v2_s

βœ…

mobilenet_edgetpu_v2_xs

βœ…

mobilenetv1_100

βœ…

mobilenetv1_100h

βœ…

mobilenetv1_125

βœ…

mobilenetv2_035

βœ…

mobilenetv2_050

βœ…

mobilenetv2_075

βœ…

mobilenetv2_100

βœ…

mobilenetv2_110d

βœ…

mobilenetv2_120d

βœ…

mobilenetv2_140

βœ…

mobilenetv3_large_075

βœ…

mobilenetv3_large_100

βœ…

mobilenetv3_large_150d

βœ…

mobilenetv3_rw

βœ…

mobilenetv3_small_050

βœ…

mobilenetv3_small_075

βœ…

mobilenetv3_small_100

βœ…

mobilenetv4_conv_aa_large

βœ…

mobilenetv4_conv_aa_medium

βœ…

mobilenetv4_conv_blur_medium

βœ…

mobilenetv4_conv_large

βœ…

mobilenetv4_conv_medium

βœ…

mobilenetv4_conv_small

βœ…

mobilenetv4_conv_small_035

βœ…

mobilenetv4_conv_small_050

βœ…

mobilenetv4_hybrid_large

βœ…

mobilenetv4_hybrid_large_075

βœ…

mobilenetv4_hybrid_medium

βœ…

mobilenetv4_hybrid_medium_075

βœ…

mobileone_s0

βœ…

mobileone_s1

βœ…

mobileone_s2

βœ…

mobileone_s3

βœ…

mobileone_s4

βœ…

mobilevit_s

βœ…

mobilevit_xs

βœ…

mobilevit_xxs

βœ…

mobilevitv2_050

βœ…

mobilevitv2_075

βœ…

mobilevitv2_100

βœ…

mobilevitv2_125

βœ…

mobilevitv2_150

βœ…

mobilevitv2_175

βœ…

mobilevitv2_200

βœ…

nf_ecaresnet26

βœ…

nf_ecaresnet50

βœ…

nf_ecaresnet101

βœ…

nf_regnet_b0

βœ…

nf_regnet_b1

βœ…

nf_regnet_b2

βœ…

nf_regnet_b3

βœ…

nf_regnet_b4

βœ…

nf_regnet_b5

βœ…

nf_resnet26

βœ…

nf_resnet50

βœ…

nf_resnet101

βœ…

nf_seresnet26

βœ…

nf_seresnet50

βœ…

nf_seresnet101

βœ…

nfnet_f0

βœ…

nfnet_f1

βœ…

nfnet_f2

βœ…

nfnet_f3

βœ…

nfnet_f4

βœ…

nfnet_f5

βœ…

nfnet_f6

βœ…

nfnet_f7

βœ…

nfnet_l0

βœ…

regnetv_040

βœ…

regnetv_064

βœ…

regnetx_002

βœ…

regnetx_004

βœ…

regnetx_004_tv

βœ…

regnetx_006

βœ…

regnetx_008

βœ…

regnetx_016

βœ…

regnetx_032

βœ…

regnetx_040

βœ…

regnetx_064

βœ…

regnetx_080

βœ…

regnetx_120

βœ…

regnetx_160

βœ…

regnetx_320

βœ…

regnety_002

βœ…

regnety_004

βœ…

regnety_006

βœ…

regnety_008

βœ…

regnety_008_tv

βœ…

regnety_016

βœ…

regnety_032

βœ…

regnety_040

βœ…

regnety_040_sgn

βœ…

regnety_064

βœ…

regnety_080

βœ…

regnety_080_tv

βœ…

regnety_120

βœ…

regnety_160

βœ…

regnety_320

βœ…

regnety_640

βœ…

regnety_1280

βœ…

regnety_2560

βœ…

regnetz_005

βœ…

regnetz_040

βœ…

regnetz_040_h

βœ…

regnetz_b16

βœ…

regnetz_b16_evos

βœ…

regnetz_c16

βœ…

regnetz_c16_evos

βœ…

regnetz_d8

βœ…

regnetz_d8_evos

βœ…

regnetz_d32

βœ…

regnetz_e8

βœ…

repghostnet_050

repghostnet_058

repghostnet_080

repghostnet_100

repghostnet_111

repghostnet_130

repghostnet_150

repghostnet_200

repvgg_a0

βœ…

repvgg_a1

βœ…

repvgg_a2

βœ…

repvgg_b0

βœ…

repvgg_b1

βœ…

repvgg_b1g4

βœ…

repvgg_b2

βœ…

repvgg_b2g4

βœ…

repvgg_b3

βœ…

repvgg_b3g4

βœ…

repvgg_d2se

βœ…

res2net50_14w_8s

βœ…

res2net50_26w_4s

βœ…

res2net50_26w_6s

βœ…

res2net50_26w_8s

βœ…

res2net50_48w_2s

βœ…

res2net50d

βœ…

res2net101_26w_4s

βœ…

res2net101d

βœ…

res2next50

βœ…

resnest14d

βœ…

resnest26d

βœ…

resnest50d

βœ…

resnest50d_1s4x24d

βœ…

resnest50d_4s2x40d

βœ…

resnest101e

βœ…

resnest200e

βœ…

resnest269e

βœ…

resnet10t

βœ…

resnet14t

βœ…

resnet18

βœ…

resnet18d

βœ…

resnet26

βœ…

resnet26d

βœ…

resnet26t

βœ…

resnet32ts

βœ…

resnet33ts

βœ…

resnet34

βœ…

resnet34d

βœ…

resnet50

βœ…

resnet50_clip

βœ…

resnet50_clip_gap

βœ…

resnet50_gn

βœ…

resnet50_mlp

βœ…

resnet50c

βœ…

resnet50d

βœ…

resnet50s

βœ…

resnet50t

βœ…

resnet50x4_clip

βœ…

resnet50x4_clip_gap

βœ…

resnet50x16_clip

βœ…

resnet50x16_clip_gap

βœ…

resnet50x64_clip

βœ…

resnet50x64_clip_gap

βœ…

resnet51q

βœ…

resnet61q

βœ…

resnet101

βœ…

resnet101_clip

βœ…

resnet101_clip_gap

βœ…

resnet101c

βœ…

resnet101d

βœ…

resnet101s

βœ…

resnet152

βœ…

resnet152c

βœ…

resnet152d

βœ…

resnet152s

βœ…

resnet200

βœ…

resnet200d

βœ…

resnetaa34d

βœ…

resnetaa50

βœ…

resnetaa50d

βœ…

resnetaa101d

βœ…

resnetblur18

βœ…

resnetblur50

βœ…

resnetblur50d

βœ…

resnetblur101d

βœ…

resnetrs50

βœ…

resnetrs101

βœ…

resnetrs152

βœ…

resnetrs200

βœ…

resnetrs270

βœ…

resnetrs350

βœ…

resnetrs420

βœ…

resnetv2_18

βœ…

resnetv2_18d

βœ…

resnetv2_34

βœ…

resnetv2_34d

βœ…

resnetv2_50

βœ…

resnetv2_50d

βœ…

resnetv2_50d_evos

βœ…

resnetv2_50d_frn

βœ…

resnetv2_50d_gn

βœ…

resnetv2_50t

βœ…

resnetv2_50x1_bit

βœ…

resnetv2_50x3_bit

βœ…

resnetv2_101

βœ…

resnetv2_101d

βœ…

resnetv2_101x1_bit

βœ…

resnetv2_101x3_bit

βœ…

resnetv2_152

βœ…

resnetv2_152d

βœ…

resnetv2_152x2_bit

βœ…

resnetv2_152x4_bit

βœ…

resnext26ts

βœ…

resnext50_32x4d

βœ…

resnext50d_32x4d

βœ…

resnext101_32x4d

βœ…

resnext101_32x8d

βœ…

resnext101_32x16d

βœ…

resnext101_32x32d

βœ…

resnext101_64x4d

βœ…

rexnet_100

βœ…

rexnet_130

βœ…

rexnet_150

βœ…

rexnet_200

βœ…

rexnet_300

βœ…

rexnetr_100

βœ…

rexnetr_130

βœ…

rexnetr_150

βœ…

rexnetr_200

βœ…

rexnetr_300

βœ…

sebotnet33ts_256

βœ…

sedarknet21

βœ…

sehalonet33ts

βœ…

selecsls42

selecsls42b

selecsls60

selecsls60b

selecsls84

semnasnet_050

βœ…

semnasnet_075

βœ…

semnasnet_100

βœ…

semnasnet_140

βœ…

senet154

βœ…

seresnet18

βœ…

seresnet33ts

βœ…

seresnet34

βœ…

seresnet50

βœ…

seresnet50t

βœ…

seresnet101

βœ…

seresnet152

βœ…

seresnet152d

βœ…

seresnet200d

βœ…

seresnet269d

βœ…

seresnetaa50d

βœ…

seresnext26d_32x4d

βœ…

seresnext26t_32x4d

βœ…

seresnext26ts

βœ…

seresnext50_32x4d

βœ…

seresnext101_32x4d

βœ…

seresnext101_32x8d

βœ…

seresnext101_64x4d

βœ…

seresnext101d_32x8d

βœ…

seresnextaa101d_32x8d

βœ…

seresnextaa201d_32x8d

βœ…

skresnet18

βœ…

skresnet34

βœ…

skresnet50

βœ…

skresnet50d

βœ…

skresnext50_32x4d

βœ…

spnasnet_100

βœ…

tf_efficientnet_b0

βœ…

tf_efficientnet_b1

βœ…

tf_efficientnet_b2

βœ…

tf_efficientnet_b3

βœ…

tf_efficientnet_b4

βœ…

tf_efficientnet_b5

βœ…

tf_efficientnet_b6

βœ…

tf_efficientnet_b7

βœ…

tf_efficientnet_b8

βœ…

tf_efficientnet_cc_b0_4e

βœ…

tf_efficientnet_cc_b0_8e

βœ…

tf_efficientnet_cc_b1_8e

βœ…

tf_efficientnet_el

βœ…

tf_efficientnet_em

βœ…

tf_efficientnet_es

βœ…

tf_efficientnet_l2

βœ…

tf_efficientnet_lite0

βœ…

tf_efficientnet_lite1

βœ…

tf_efficientnet_lite2

βœ…

tf_efficientnet_lite3

βœ…

tf_efficientnet_lite4

βœ…

tf_efficientnetv2_b0

βœ…

tf_efficientnetv2_b1

βœ…

tf_efficientnetv2_b2

βœ…

tf_efficientnetv2_b3

βœ…

tf_efficientnetv2_l

βœ…

tf_efficientnetv2_m

βœ…

tf_efficientnetv2_s

βœ…

tf_efficientnetv2_xl

βœ…

tf_mixnet_l

βœ…

tf_mixnet_m

βœ…

tf_mixnet_s

βœ…

tf_mobilenetv3_large_075

βœ…

tf_mobilenetv3_large_100

βœ…

tf_mobilenetv3_large_minimal_100

βœ…

tf_mobilenetv3_small_075

βœ…

tf_mobilenetv3_small_100

βœ…

tf_mobilenetv3_small_minimal_100

βœ…

tinynet_a

βœ…

tinynet_b

βœ…

tinynet_c

βœ…

tinynet_d

βœ…

tinynet_e

βœ…

vgg11

vgg11_bn

vgg13

vgg13_bn

vgg16

vgg16_bn

vgg19

vgg19_bn

vovnet39a

vovnet57a

wide_resnet50_2

βœ…

wide_resnet101_2

βœ…

xception41

βœ…

xception41p

βœ…

xception65

βœ…

xception65p

βœ…

xception71

βœ…

Transformer-Style#

Transformer-style models (e.g., Swin Transformer, ConvNeXt) typically produce feature maps starting at a 1/4 scale, followed by 1/8, 1/16, and 1/32 scales

Encoder name

Support dilation

caformer_b36

caformer_m36

caformer_s18

caformer_s36

convformer_b36

convformer_m36

convformer_s18

convformer_s36

convnext_atto

βœ…

convnext_atto_ols

βœ…

convnext_atto_rms

βœ…

convnext_base

βœ…

convnext_femto

βœ…

convnext_femto_ols

βœ…

convnext_large

βœ…

convnext_large_mlp

βœ…

convnext_nano

βœ…

convnext_nano_ols

βœ…

convnext_pico

βœ…

convnext_pico_ols

βœ…

convnext_small

βœ…

convnext_tiny

βœ…

convnext_tiny_hnf

βœ…

convnext_xlarge

βœ…

convnext_xxlarge

βœ…

convnext_zepto_rms

βœ…

convnext_zepto_rms_ols

βœ…

convnextv2_atto

βœ…

convnextv2_base

βœ…

convnextv2_femto

βœ…

convnextv2_huge

βœ…

convnextv2_large

βœ…

convnextv2_nano

βœ…

convnextv2_pico

βœ…

convnextv2_small

βœ…

convnextv2_tiny

βœ…

davit_base

davit_base_fl

davit_giant

davit_huge

davit_huge_fl

davit_large

davit_small

davit_tiny

edgenext_base

edgenext_small

edgenext_small_rw

edgenext_x_small

edgenext_xx_small

efficientformer_l1

efficientformer_l3

efficientformer_l7

efficientformerv2_l

efficientformerv2_s0

efficientformerv2_s1

efficientformerv2_s2

efficientvit_b0

efficientvit_b1

efficientvit_b2

efficientvit_b3

efficientvit_l1

efficientvit_l2

efficientvit_l3

fastvit_ma36

fastvit_mci0

fastvit_mci1

fastvit_mci2

fastvit_s12

fastvit_sa12

fastvit_sa24

fastvit_sa36

fastvit_t8

fastvit_t12

focalnet_base_lrf

focalnet_base_srf

focalnet_huge_fl3

focalnet_huge_fl4

focalnet_large_fl3

focalnet_large_fl4

focalnet_small_lrf

focalnet_small_srf

focalnet_tiny_lrf

focalnet_tiny_srf

focalnet_xlarge_fl3

focalnet_xlarge_fl4

hgnet_base

hgnet_small

hgnet_tiny

hgnetv2_b0

hgnetv2_b1

hgnetv2_b2

hgnetv2_b3

hgnetv2_b4

hgnetv2_b5

hgnetv2_b6

hiera_base_224

hiera_base_abswin_256

hiera_base_plus_224

hiera_huge_224

hiera_large_224

hiera_small_224

hiera_small_abswin_256

hiera_tiny_224

hieradet_small

inception_next_base

inception_next_small

inception_next_tiny

mambaout_base

mambaout_base_plus_rw

mambaout_base_short_rw

mambaout_base_tall_rw

mambaout_base_wide_rw

mambaout_femto

mambaout_kobe

mambaout_small

mambaout_small_rw

mambaout_tiny

mvitv2_base

mvitv2_base_cls

mvitv2_huge_cls

mvitv2_large

mvitv2_large_cls

mvitv2_small

mvitv2_small_cls

mvitv2_tiny

nest_base

nest_base_jx

nest_small

nest_small_jx

nest_tiny

nest_tiny_jx

nextvit_base

nextvit_large

nextvit_small

poolformer_m36

poolformer_m48

poolformer_s12

poolformer_s24

poolformer_s36

poolformerv2_m36

poolformerv2_m48

poolformerv2_s12

poolformerv2_s24

poolformerv2_s36

pvt_v2_b0

pvt_v2_b1

pvt_v2_b2

pvt_v2_b2_li

pvt_v2_b3

pvt_v2_b4

pvt_v2_b5

rdnet_base

rdnet_large

rdnet_small

rdnet_tiny

repvit_m0_9

repvit_m1

repvit_m1_0

repvit_m1_1

repvit_m1_5

repvit_m2

repvit_m2_3

repvit_m3

sam2_hiera_base_plus

sam2_hiera_large

sam2_hiera_small

sam2_hiera_tiny

swin_base_patch4_window7_224

swin_base_patch4_window12_384

swin_large_patch4_window7_224

swin_large_patch4_window12_384

swin_s3_base_224

swin_s3_small_224

swin_s3_tiny_224

swin_small_patch4_window7_224

swin_tiny_patch4_window7_224

swinv2_base_window8_256

swinv2_base_window12_192

swinv2_base_window12to16_192to256

swinv2_base_window12to24_192to384

swinv2_base_window16_256

swinv2_cr_base_224

swinv2_cr_base_384

swinv2_cr_base_ns_224

swinv2_cr_giant_224

swinv2_cr_giant_384

swinv2_cr_huge_224

swinv2_cr_huge_384

swinv2_cr_large_224

swinv2_cr_large_384

swinv2_cr_small_224

swinv2_cr_small_384

swinv2_cr_small_ns_224

swinv2_cr_small_ns_256

swinv2_cr_tiny_224

swinv2_cr_tiny_384

swinv2_cr_tiny_ns_224

swinv2_large_window12_192

swinv2_large_window12to16_192to256

swinv2_large_window12to24_192to384

swinv2_small_window8_256

swinv2_small_window16_256

swinv2_tiny_window8_256

swinv2_tiny_window16_256

tiny_vit_5m_224

tiny_vit_11m_224

tiny_vit_21m_224

tiny_vit_21m_384

tiny_vit_21m_512

tresnet_l

tresnet_m

tresnet_v2_l

tresnet_xl

twins_pcpvt_base

twins_pcpvt_large

twins_pcpvt_small

twins_svt_base

twins_svt_large

twins_svt_small