Add support for fine-tuning CLIP-like models using contrastive-image-text example

src/transformers/models/auto/configuration_auto.py

@@ -54,6 +54,7 @@
         ("camembert", "CamembertConfig"),
         ("canine", "CanineConfig"),
         ("chinese_clip", "ChineseCLIPConfig"),
+        ("chinese_clip_vision_model", "ChineseCLIPVisionConfig"),
         ("clap", "ClapConfig"),
         ("clip", "CLIPConfig"),
         ("clip_vision_model", "CLIPVisionConfig"),
@@ -512,6 +513,7 @@
         ("camembert", "CamemBERT"),
         ("canine", "CANINE"),
         ("chinese_clip", "Chinese-CLIP"),
+        ("chinese_clip_vision_model", "ChineseCLIPVisionModel"),
         ("clap", "CLAP"),
         ("clip", "CLIP"),
         ("clip_vision_model", "CLIPVisionModel"),
@@ -773,6 +775,7 @@
         ("xclip", "x_clip"),
         ("clip_vision_model", "clip"),
         ("siglip_vision_model", "siglip"),
+        ("chinese_clip_vision_model", "chinese_clip"),
     ]
 )
 

src/transformers/models/auto/modeling_auto.py

@@ -57,6 +57,7 @@
         ("camembert", "CamembertModel"),
         ("canine", "CanineModel"),
         ("chinese_clip", "ChineseCLIPModel"),
+        ("chinese_clip_vision_model", "ChineseCLIPVisionModel"),
         ("clap", "ClapModel"),
         ("clip", "CLIPModel"),
         ("clip_vision_model", "CLIPVisionModel"),

src/transformers/models/chinese_clip/configuration_chinese_clip.py

@@ -171,8 +171,7 @@ class ChineseCLIPVisionConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`ChineseCLIPModel`]. It is used to instantiate an
     ChineseCLIP model according to the specified arguments, defining the model architecture. Instantiating a
     configuration with the defaults will yield a similar configuration to that of the ChineseCLIP
-    [OFA-Sys/chinese-clip-vit-base-patch16](https:
-        //huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16) architecture.
+    [OFA-Sys/chinese-clip-vit-base-patch16](https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16) architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
     documentation from [`PretrainedConfig`] for more information.

src/transformers/models/vision_text_dual_encoder/configuration_vision_text_dual_encoder.py

@@ -18,11 +18,19 @@
 from ...configuration_utils import PretrainedConfig
 from ...utils import logging
 from ..auto.configuration_auto import AutoConfig
+from ..chinese_clip.configuration_chinese_clip import ChineseCLIPVisionConfig
 from ..clip.configuration_clip import CLIPVisionConfig
+from ..siglip.configuration_siglip import SiglipVisionConfig
 
 
 logger = logging.get_logger(__name__)
 
+VISION_MODEL_CONFIGS = {
+    "clip_vision_model": CLIPVisionConfig,
+    "chinese_clip_vision_model": ChineseCLIPVisionConfig,
+    "siglip_vision_model": SiglipVisionConfig,
+}
+
 
 class VisionTextDualEncoderConfig(PretrainedConfig):
     r"""
@@ -85,12 +93,13 @@ def __init__(self, projection_dim=512, logit_scale_init_value=2.6592, **kwargs):
         vision_model_type = vision_config.pop("model_type")
         text_model_type = text_config.pop("model_type")
 
-        if vision_model_type == "clip":
-            self.vision_config = AutoConfig.for_model(vision_model_type, **vision_config).vision_config
-        elif vision_model_type == "clip_vision_model":
-            self.vision_config = CLIPVisionConfig(**vision_config)
+        vision_config_class = VISION_MODEL_CONFIGS.get(vision_model_type)
+        if vision_config_class is not None:
+            self.vision_config = vision_config_class(**vision_config)
         else:
             self.vision_config = AutoConfig.for_model(vision_model_type, **vision_config)
+            if hasattr(self.vision_config, "vision_config"):
+                self.vision_config = self.vision_config.vision_config
 
         self.text_config = AutoConfig.for_model(text_model_type, **text_config)
 

utils/check_copies.py

@@ -1070,6 +1070,7 @@ def check_model_list_copy(overwrite: bool = False):
     "VisionTextDualEncoder",
     "CLIPVisionModel",
     "SiglipVisionModel",
+    "ChineseCLIPVisionModel",
 ]
 
 # Template for new entries to add in the main README when we have missing models.

utils/check_table.py

@@ -171,7 +171,7 @@ def _center_text(text: str, width: int) -> str:
     "XLS-R": "Wav2Vec2",
     "XLSR-Wav2Vec2": "Wav2Vec2",
 }
-MODEL_NAMES_TO_IGNORE = ["CLIPVisionModel", "SiglipVisionModel"]
+MODEL_NAMES_TO_IGNORE = ["CLIPVisionModel", "SiglipVisionModel", "ChineseCLIPVisionModel"]
 
 
 def get_model_table_from_auto_modules() -> str: