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Add remaining sbb vit betwixt/mediumd fine-tunes

sbb2_vit_hiera_weights
Ross Wightman 2024-08-21 10:09:38 -07:00
parent dc94cca0e5
commit 9fcbf39cdc
1 changed files with 34 additions and 0 deletions

34
timm/models/vision_transformer.py
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@ -1964,6 +1964,9 @@ default_cfgs = {
hf_hub_id='timm/',
num_classes=11821,
input_size=(3, 256, 256), crop_pct=0.95),
'vit_mediumd_patch16_reg4_gap_256.sbb2_e200_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 256, 256), crop_pct=0.95),
'vit_mediumd_patch16_reg4_gap_256.sbb_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 256, 256), crop_pct=0.95),
@ -1975,9 +1978,15 @@ default_cfgs = {
hf_hub_id='timm/',
num_classes=11821,
input_size=(3, 256, 256), crop_pct=0.95),
'vit_mediumd_patch16_reg4_gap_384.sbb2_e200_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 384, 384), crop_pct=1.0),
'vit_betwixt_patch16_reg1_gap_256.sbb_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 256, 256), crop_pct=0.95),
'vit_betwixt_patch16_reg4_gap_256.sbb2_e200_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 256, 256), crop_pct=0.95),
'vit_betwixt_patch16_reg4_gap_256.sbb_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 256, 256), crop_pct=0.95),
@ -1992,6 +2001,9 @@ default_cfgs = {
hf_hub_id='timm/',
num_classes=11821,
input_size=(3, 256, 256), crop_pct=0.95),
'vit_betwixt_patch16_reg4_gap_384.sbb2_e200_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 384, 384), crop_pct=1.0),
'vit_base_patch16_reg4_gap_256.untrained': _cfg(
input_size=(3, 256, 256)),
@ -3118,6 +3130,17 @@ def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> Visi
return model
@register_model
def vit_mediumd_patch16_reg4_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(
patch_size=16, embed_dim=512, depth=20, num_heads=8, init_values=1e-5,
class_token=False, no_embed_class=True, reg_tokens=4, global_pool='avg',
)
model = _create_vision_transformer(
'vit_mediumd_patch16_reg4_gap_384', pretrained=pretrained, **dict(model_args, **kwargs))
return model
@register_model
def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(
@ -3140,6 +3163,17 @@ def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> Visi
return model
@register_model
def vit_betwixt_patch16_reg4_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(
patch_size=16, embed_dim=640, depth=12, num_heads=10, init_values=1e-5,
class_token=False, no_embed_class=True, reg_tokens=4, global_pool='avg',
)
model = _create_vision_transformer(
'vit_betwixt_patch16_reg4_gap_384', pretrained=pretrained, **dict(model_args, **kwargs))
return model
@register_model
def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(