models.py

model_lists = [
'vit_huge_patch14_clip_224',
'vit_large_patch14_clip_224',
'vit_base_patch8_224',
'deit3_large_patch16_224',
'beitv2_large_patch16_224',
'hiera_huge_224',
'hgnetv2_b6',
'nextvit_large',
'nextvit_base',
'nextvit_small',
'convnext_tiny',
'convnext_small',
'convnextv2_tiny',
'convnextv2_base',
'convnextv2_large',
'caformer_s18',
'caformer_s36',
'caformer_b36',
'maxvit_rmlp_base_rw_224',
'maxvit_small_tf_224',
'maxxvitv2_rmlp_base_rw_224',
'coatnet_2_rw_224',
'coatnet_rmlp_1_rw2_224',
'coatnet_rmlp_2_rw_224',
'swin_large_patch4_window7_224',
'convformer_m36',
'convformer_s36',
'tiny_vit_11m_224',
'tiny_vit_21m_224',
'efficientvit_l1',
'efficientvit_l2',
'efficientvit_b0',
'efficientvit_b1',
'efficientvit_b2',
'hgnetv2_b2',
'hgnetv2_b3',
'hgnetv2_b4',
'hgnetv2_b5',
'rexnet_130',
'rexnet_150',
'rexnet_200',
'rexnetr_200',
'rexnetr_300',
'efficientformerv2_l',
'efficientformerv2_s1',
'efficientformerv2_s2',
'levit_256',
'levit_conv_128',
'levit_conv_192',
'levit_conv_256',
'repvit_m1_0',
'mobilenetv3_small_050',
'tf_mobilenetv3_small_100',
'mobilenetv3_large_100',
'mobilenetv4_hybrid_medium',
'mixnet_xl',
'tf_mixnet_l',
'mixnet_l',
'repghostnet_050',
'repghostnet_058',
'repghostnet_080',
'repghostnet_100',
'repghostnet_111',
'repghostnet_200',
'fbnetv3_b',
'fbnetv3_d',
'efficientnet_b0',
'tf_efficientnet_b0',
'tf_efficientnet_cc_b0_4e',
'hardcorenas_f',
'hardcorenas_e',
'hardcorenas_c',
'hrnet_w18_small_v2',
'ghostnet_100',
'eva_giant_patch14_224'
]