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Add 448 so150m2 weight/model, add updated internvit 300m weight

pull/2441/head
Ross Wightman 2025-02-17 12:59:10 -08:00
parent 9ce824c39a
commit 7234f5c6c5
2 changed files with 21 additions and 1 deletions

2
timm/models/_hub.py
View File

@ -395,7 +395,7 @@ def push_to_hf_hub(
def generate_readme(model_card: dict, model_name: str):
tags = model_card.get('tags', None) or ['image-classification', 'timm']
tags = model_card.get('tags', None) or ['image-classification', 'timm', 'transformers']
readme_text = "---\n"
if tags:
readme_text += "tags:\n"

20
timm/models/vision_transformer.py
View File

@ -2174,12 +2174,20 @@ default_cfgs = {
'vit_so150m2_patch16_reg1_gap_384.sbb_e200_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 384, 384), crop_pct=1.0),
'vit_so150m2_patch16_reg1_gap_448.sbb_e200_in12k_ft_in1k': _cfg(
hf_hub_id='timm/',
input_size=(3, 448, 448), crop_pct=1.0, crop_mode='squash'),
'vit_intern300m_patch14_448.ogvl_dist': _cfg(
hf_hub_id='timm/',
mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD,
input_size=(3, 448, 448), crop_pct=1.0, num_classes=0,
),
'vit_intern300m_patch14_448.ogvl_2pt5': _cfg(
hf_hub_id='timm/',
mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD,
input_size=(3, 448, 448), crop_pct=1.0, num_classes=0,
),
'aimv2_large_patch14_224.apple_pt': _cfg(
hf_hub_id='timm/',
@ -3538,6 +3546,18 @@ def vit_so150m2_patch16_reg1_gap_384(pretrained: bool = False, **kwargs) -> Visi
return model
@register_model
def vit_so150m2_patch16_reg1_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
""" SO150M v2 (shape optimized, but diff than paper def, optimized for GPU) """
model_args = dict(
patch_size=16, embed_dim=832, depth=21, num_heads=13, mlp_ratio=34/13, init_values=1e-5,
qkv_bias=False, class_token=False, reg_tokens=1, global_pool='avg',
)
model = _create_vision_transformer(
'vit_so150m2_patch16_reg1_gap_448', pretrained=pretrained, **dict(model_args, **kwargs))
return model
@register_model
def vit_intern300m_patch14_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(