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add tinyclip 8m

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Thien Tran 2024-03-19 07:02:17 +08:00
parent 6ccb7d6a7c
commit dfffffac55
1 changed files with 14 additions and 0 deletions
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14
timm/models/vision_transformer.py
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@ -1015,6 +1015,8 @@ def checkpoint_filter_fn(
return _convert_openai_clip(state_dict, model)
elif 'module.visual.class_embedding' in state_dict:
return _convert_openai_clip(state_dict, model, prefix='module.visual.')
elif '_image_encoder.module.visual.class_embedding' in state_dict:
return _convert_openai_clip(state_dict, model, prefix='_image_encoder.module.visual.')
if "mask_token" in state_dict:
state_dict = _convert_dinov2(state_dict, model)
@ -1735,6 +1737,10 @@ default_cfgs = {
input_size=(3, 384, 384),
num_classes=0),
'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',
mean=OPENAI_CLIP_MEAN, std=OPENAI_CLIP_STD, num_classes=512),
'vit_medium_patch16_reg4_256': _cfg(
input_size=(3, 256, 256)),
'vit_medium_patch16_reg4_gap_256': _cfg(
@ -2621,6 +2627,14 @@ def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionT
return model
@register_model
def vit_8m_patch16_tinyclip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
model_args = dict(embed_dim=256, depth=10, num_heads=4, pre_norm=True, norm_layer=nn.LayerNorm)
model = _create_vision_transformer(
'vit_8m_patch16_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(