Updating remaining licenses

Author: alexanderdann

timm/models/_hub.py

@@ -578,4 +578,11 @@ def _get_license_from_hf_hub(model_id: str | None, hf_hub_id: str | None) -> str
         return None
 
     license = info.card_data.get("license").lower() if info.card_data else None
+
+    if license == 'other':
+        name = info.card_data.get("license_name", None)
+
+        if name is not None:
+            return name
+
     return license

timm/models/byobnet.py

@@ -2606,31 +2606,31 @@ def _cfgr(url: str = '', **kwargs) -> Dict[str, Any]:
         hf_hub_id='timm/',
         crop_pct=0.875,
         first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'),
-        license='other',
+        license='mobileone-license',
     ),
     'mobileone_s1.apple_in1k': _cfg(
         hf_hub_id='timm/',
         crop_pct=0.9,
         first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'),
-        license='other',
+        license='mobileone-license',
     ),
     'mobileone_s2.apple_in1k': _cfg(
         hf_hub_id='timm/',
         crop_pct=0.9,
         first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'),
-        license='other',
+        license='mobileone-license',
     ),
     'mobileone_s3.apple_in1k': _cfg(
         hf_hub_id='timm/',
         crop_pct=0.9,
         first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'),
-        license='other',
+        license='mobileone-license',
     ),
     'mobileone_s4.apple_in1k': _cfg(
         hf_hub_id='timm/',
         crop_pct=0.9,
         first_conv=('stem.conv_kxk.0.conv', 'stem.conv_scale.conv'),
-        license='other',
+        license='mobileone-license',
     ),
 
     # original attention pool head variants

timm/models/convnext.py

@@ -1113,25 +1113,25 @@ def _cfgv2(url='', **kwargs):
         hf_hub_id='timm/',
         crop_pct=1.0,
         num_classes=0,
-        license='dinov3',
+        license='dinov3-license',
     ),
     'convnext_small.dinov3_lvd1689m': _cfg(
         hf_hub_id='timm/',
         crop_pct=1.0,
         num_classes=0,
-        license='dinov3',
+        license='dinov3-license',
     ),
     'convnext_base.dinov3_lvd1689m': _cfg(
         hf_hub_id='timm/',
         crop_pct=1.0,
         num_classes=0,
-        license='dinov3',
+        license='dinov3-license',
     ),
     'convnext_large.dinov3_lvd1689m': _cfg(
         hf_hub_id='timm/',
         crop_pct=1.0,
         num_classes=0,
-        license='dinov3',
+        license='dinov3-license',
     ),
 
     "test_convnext.r160_in1k": _cfg(

timm/models/eva.py

@@ -1305,7 +1305,7 @@ def _dinov3_cfg(url: str = '', **kwargs) -> Dict[str, Any]:
         'crop_pct': 1.0, 'interpolation': 'bicubic', 'fixed_input_size': True,
         'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
         'first_conv': 'patch_embed.proj', 'classifier': 'head',
-        'license': 'dinov3', **kwargs
+        'license': 'dinov3-license', **kwargs
     }
 
 default_cfgs = generate_default_cfgs({
@@ -2567,7 +2567,7 @@ def vit_large_patch16_rope_ape_224(pretrained: bool = False, **kwargs) -> Eva:
         rope_grid_indexing='xy',
         rope_temperature=100.0,
     )
-    
+
     model = _create_eva('vit_large_patch16_rope_ape_224', pretrained=pretrained, **dict(model_args, **kwargs))
     return model
 

timm/models/fastvit.py

@@ -1434,7 +1434,7 @@ def _cfg(url="", **kwargs):
         "license": "other",
         "std": IMAGENET_DEFAULT_STD,
         'first_conv': ('stem.0.conv_kxk.0.conv', 'stem.0.conv_scale.conv'),
-        "classifier": "head.fc",
+        "classifier": "head.fc", "license": "fastvit-license",
         **kwargs,
     }
 
@@ -1482,21 +1482,21 @@ def _cfg(url="", **kwargs):
         url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_s0.pt',
         crop_pct=0.95,
         num_classes=512,  # CLIP proj dim
-        mean=(0., 0., 0.), std=(1., 1., 1.), license=None,
+        mean=(0., 0., 0.), std=(1., 1., 1.), license='apple-amlr'
     ),
     "fastvit_mci1.apple_mclip": _cfg(
         hf_hub_id='apple/mobileclip_s1_timm',
         url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_s1.pt',
         crop_pct=0.95,
         num_classes=512,  # CLIP proj dim
-        mean=(0., 0., 0.), std=(1., 1., 1.), license=None,
+        mean=(0., 0., 0.), std=(1., 1., 1.), license='apple-amlr'
     ),
     "fastvit_mci2.apple_mclip": _cfg(
         hf_hub_id='apple/mobileclip_s2_timm',
         url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_s2.pt',
         crop_pct=0.95,
         num_classes=512,  # CLIP proj dim
-        mean=(0., 0., 0.), std=(1., 1., 1.), license=None,
+        mean=(0., 0., 0.), std=(1., 1., 1.), license='apple-amlr'
     ),
 
     "fastvit_mci0.apple_mclip2_dfndr2b": _cfg(

timm/models/mobilevit.py

@@ -595,7 +595,7 @@ def _cfg(url='', **kwargs):
         'mean': (0., 0., 0.), 'std': (1., 1., 1.),
         'first_conv': 'stem.conv', 'classifier': 'head.fc',
         'fixed_input_size': False,
-        'license': 'other',
+        'license': 'cvnets-license',
         **kwargs
     }
 

timm/models/regnet.py

@@ -1195,37 +1195,37 @@ def _cfgtv2(url: str = '', **kwargs) -> Dict[str, Any]:
 
     'regnety_320.seer_ft_in1k': _cfgtv2(
         hf_hub_id='timm/',
-        license='other', origin_url='https://github.com/facebookresearch/vissl',
+        license='seer-license', origin_url='https://github.com/facebookresearch/vissl',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/seer_finetuned/seer_regnet32_finetuned_in1k_model_final_checkpoint_phase78.torch',
         input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
     'regnety_640.seer_ft_in1k': _cfgtv2(
         hf_hub_id='timm/',
-        license='other', origin_url='https://github.com/facebookresearch/vissl',
+        license='seer-license', origin_url='https://github.com/facebookresearch/vissl',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/seer_finetuned/seer_regnet64_finetuned_in1k_model_final_checkpoint_phase78.torch',
         input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
     'regnety_1280.seer_ft_in1k': _cfgtv2(
         hf_hub_id='timm/',
-        license='other', origin_url='https://github.com/facebookresearch/vissl',
+        license='seer-license', origin_url='https://github.com/facebookresearch/vissl',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/seer_finetuned/seer_regnet128_finetuned_in1k_model_final_checkpoint_phase78.torch',
         input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
     'regnety_2560.seer_ft_in1k': _cfgtv2(
         hf_hub_id='timm/',
-        license='other', origin_url='https://github.com/facebookresearch/vissl',
+        license='seer-license', origin_url='https://github.com/facebookresearch/vissl',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/seer_finetuned/seer_regnet256_finetuned_in1k_model_final_checkpoint_phase38.torch',
         input_size=(3, 384, 384), pool_size=(12, 12), crop_pct=1.0),
 
     'regnety_320.seer': _cfgtv2(
         hf_hub_id='timm/',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/seer_regnet32d/seer_regnet32gf_model_iteration244000.torch',
-        num_classes=0, license='other', origin_url='https://github.com/facebookresearch/vissl'),
+        num_classes=0, license='seer-license', origin_url='https://github.com/facebookresearch/vissl'),
     'regnety_640.seer': _cfgtv2(
         hf_hub_id='timm/',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/seer_regnet64/seer_regnet64gf_model_final_checkpoint_phase0.torch',
-        num_classes=0, license='other', origin_url='https://github.com/facebookresearch/vissl'),
+        num_classes=0, license='seer-license', origin_url='https://github.com/facebookresearch/vissl'),
     'regnety_1280.seer': _cfgtv2(
         hf_hub_id='timm/',
         url='https://dl.fbaipublicfiles.com/vissl/model_zoo/swav_ig1b_regnet128Gf_cnstant_bs32_node16_sinkhorn10_proto16k_syncBN64_warmup8k/model_final_checkpoint_phase0.torch',
-        num_classes=0, license='other', origin_url='https://github.com/facebookresearch/vissl'),
+        num_classes=0, license='seer-license', origin_url='https://github.com/facebookresearch/vissl'),
     # FIXME invalid weight <-> model match, mistake on their end
     #'regnety_2560.seer': _cfgtv2(
     #    url='https://dl.fbaipublicfiles.com/vissl/model_zoo/swav_ig1b_cosine_rg256gf_noBNhead_wd1e5_fairstore_bs16_node64_sinkhorn10_proto16k_apex_syncBN64_warmup8k/model_final_checkpoint_phase0.torch',
@@ -1486,4 +1486,4 @@ def regnetz_040_h(pretrained: bool = False, **kwargs) -> RegNet:
 
 register_model_deprecations(__name__, {
     'regnetz_040h': 'regnetz_040_h',
-})
+})

timm/models/senet.py

@@ -448,7 +448,7 @@ def _cfg(url='', **kwargs):
         'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
         'crop_pct': 0.875, 'interpolation': 'bilinear',
         'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
-        'first_conv': 'layer0.conv1', 'classifier': 'last_linear',
+        'first_conv': 'layer0.conv1', 'classifier': 'last_linear', 'license': 'apache-2.0',
         **kwargs
     }
 

timm/models/vision_transformer_hybrid.py

@@ -242,14 +242,15 @@ def _cfg(url='', **kwargs):
     'vit_base_mci_224.apple_mclip_lt': _cfg(
         hf_hub_id='apple/mobileclip_b_lt_timm',
         url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_blt.pt',
-        license=None,
+        license='apple-amlr',
         num_classes=512,
         mean=(0., 0., 0.), std=(1., 1., 1.), first_conv='patch_embed.backbone.0.conv',
     ),
     'vit_base_mci_224.apple_mclip': _cfg(
         hf_hub_id='apple/mobileclip_b_timm',
         url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_b.pt',
         num_classes=512,
+        license='apple-amlr',
         mean=(0., 0., 0.), std=(1., 1., 1.), first_conv='patch_embed.backbone.0.conv',
     ),
     'vit_base_mci_224.apple_mclip2_dfndr2b': _cfg(

timm/models/vitamin.py

@@ -325,7 +325,7 @@ def _cfg(url='', **kwargs):
         'crop_pct': .9, 'interpolation': 'bicubic', 'fixed_input_size': True,
         'mean': OPENAI_CLIP_MEAN, 'std': OPENAI_CLIP_STD,
         'first_conv': 'patch_embed.backbone.stem.conv1',
-        'classifier': 'head',
+        'classifier': 'head', 'license': 'mit',
         **kwargs
     }
 
@@ -623,4 +623,4 @@ def vitamin_xlarge_384(pretrained=False, **kwargs) -> VisionTransformer:
         img_size=384, embed_dim=1152, depth=32, num_heads=16, mlp_layer=GeGluMlp, mlp_ratio=2.,
         class_token=False, global_pool='avg', pos_embed='none', embed_cfg=embed_cfg)
     model = _create_vitamin('vitamin_xlarge_384', pretrained=pretrained, **dict(model_args, **kwargs))
-    return model
+    return model