add other tinyclip

This commit is contained in:
Thien Tran 2024-03-19 07:27:09 +08:00
parent dfffffac55
commit 1a1d07d479

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@ -1739,6 +1739,19 @@ default_cfgs = {
'vit_8m_patch16_tinyclip_224.yfcc15m': _cfg(
url='https://github.com/wkcn/TinyCLIP-model-zoo/releases/download/checkpoints/TinyCLIP-ViT-8M-16-Text-3M-YFCC15M.pt',
license='mit',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_39m_patch16_tinyclip_224.yfcc15m': _cfg(
url='https://github.com/wkcn/TinyCLIP-model-zoo/releases/download/checkpoints/TinyCLIP-ViT-39M-16-Text-19M-YFCC15M.pt',
license='mit',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_40m_patch32_tinyclip_224.laion400m': _cfg(
url='https://github.com/wkcn/TinyCLIP-model-zoo/releases/download/checkpoints/TinyCLIP-ViT-40M-32-Text-19M-LAION400M.pt',
license='mit',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_61m_patch32_tinyclip_224.laion400m': _cfg(
url='https://github.com/wkcn/TinyCLIP-model-zoo/releases/download/checkpoints/TinyCLIP-ViT-61M-32-Text-29M-LAION400M.pt',
license='mit',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_medium_patch16_reg4_256': _cfg(
@ -2635,6 +2648,32 @@ def vit_8m_patch16_tinyclip_224(pretrained: bool = False, **kwargs) -> VisionTra
return model
@register_model
def vit_39m_patch16_tinyclip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(embed_dim=512, depth=12, num_heads=8, pre_norm=True, norm_layer=nn.LayerNorm)
model = _create_vision_transformer(
'vit_39m_patch16_tinyclip_224', pretrained=pretrained, **dict(model_args, **kwargs))
return model
@register_model
def vit_40m_patch32_tinyclip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(
patch_size=32, embed_dim=512, depth=12, num_heads=8, pre_norm=True, norm_layer=nn.LayerNorm)
model = _create_vision_transformer(
'vit_40m_patch32_tinyclip_224', pretrained=pretrained, **dict(model_args, **kwargs))
return model
@register_model
def vit_61m_patch32_tinyclip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(
patch_size=32, embed_dim=640, depth=12, num_heads=10, pre_norm=True, norm_layer=nn.LayerNorm)
model = _create_vision_transformer(
'vit_61m_patch32_tinyclip_224', pretrained=pretrained, **dict(model_args, **kwargs))
return model
@register_model
def vit_medium_patch16_reg4_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(