Preparing for final MobileCLIP hub locations (#893)

* Preparing for final MobileCLIP hub locations

* Push to HF hub tweaks

* Update MobileCLIP weight locations

* Final MobileCLIP weight loc in apple org

src/open_clip/pretrained.py

@@ -455,16 +455,12 @@ def _mccfg(url='', hf_hub='', **kwargs):
     ),
 
     "MobileCLIP-S1": dict(
-        datacompdr=_mccfg(
-            url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_s1.pt')),
+        datacompdr=_mccfg(hf_hub='apple/MobileCLIP-S1-OpenCLIP/')),
     "MobileCLIP-S2": dict(
-        datacompdr=_mccfg(
-            url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_s2.pt')),
+        datacompdr=_mccfg(hf_hub='apple/MobileCLIP-S2-OpenCLIP/')),
     "MobileCLIP-B": dict(
-        datacompdr=_mccfg(
-            url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_b.pt'),
-        datacompdr_lt=_mccfg(
-            url='https://docs-assets.developer.apple.com/ml-research/datasets/mobileclip/mobileclip_blt.pt'),
+        datacompdr=_mccfg(hf_hub='apple/MobileCLIP-B-OpenCLIP/'),
+        datacompdr_lt=_mccfg(hf_hub='apple/MobileCLIP-B-LT-OpenCLIP/'),
     ),
 
     "ViTamin-S": dict(

src/open_clip/push_to_hf_hub.py

@@ -98,7 +98,7 @@ def push_to_hf_hub(
     private: bool = False,
     create_pr: bool = False,
     model_card: Optional[dict] = None,
-    safe_serialization: Union[bool, str] = False,
+    safe_serialization: Union[bool, str] = 'both',
 ):
     if not isinstance(tokenizer, HFTokenizer):
         # FIXME this makes it awkward to push models with new tokenizers, come up with better soln.
@@ -173,6 +173,7 @@ def push_pretrained_to_hf_hub(
     create_pr: bool = False,
     model_card: Optional[dict] = None,
     hf_tokenizer_self: bool = False,
+    **kwargs,
 ):
     model, preprocess_eval = create_model_from_pretrained(
         model_name,
@@ -182,8 +183,11 @@ def push_pretrained_to_hf_hub(
         image_std=image_std,
         image_interpolation=image_interpolation,
         image_resize_mode=image_resize_mode,
+        **kwargs,
     )
     model_config = get_model_config(model_name)
+    if pretrained == 'openai':
+        model_config['quick_gelu'] = True
     assert model_config
 
     tokenizer = get_tokenizer(model_name)