[Bugfix] Fix Dense module loading for sentence-transformers embedding models v12

Signed-off-by: FFFfff1FFFfff <[email protected]>

Author: FFFfff1FFFfff

requirements/test.txt

@@ -968,6 +968,7 @@ setuptools==77.0.3
     # via
     #   lightning-utilities
     #   pytablewriter
+    #   torch
     #   triton
 shapely==2.1.1
     # via

vllm/transformers_utils/config.py

@@ -280,11 +280,12 @@ def thinker_uses_mrope(config: PretrainedConfig) -> bool:
 
 def is_encoder_decoder(config: PretrainedConfig) -> bool:
     """Detect if the model with this config is used as an encoder/decoder."""
-    text_config = getattr(config, "text_config", None)
-    if text_config is not None:
-        return is_encoder_decoder(text_config)
 
-    return getattr(config, "is_encoder_decoder", False)
+    def _is_encoder_decoder(config: PretrainedConfig) -> bool:
+        return getattr(config, "is_encoder_decoder", False)
+
+    return (_is_encoder_decoder(config)
+            or _is_encoder_decoder(config.get_text_config()))
 
 
 def is_interleaved(config: PretrainedConfig) -> bool:
@@ -298,13 +299,21 @@ def is_interleaved(config: PretrainedConfig) -> bool:
     return False
 
 
+def _maybe_update_auto_config_kwargs(kwargs: dict[str, Any], model_type: str):
+    """
+    Update kwargs for AutoConfig initialization based on model_type
+    """
+    if model_type in _AUTO_CONFIG_KWARGS_OVERRIDES:
+        kwargs.update(_AUTO_CONFIG_KWARGS_OVERRIDES[model_type])
+    return kwargs
+
+
 def _maybe_remap_hf_config_attrs(config: PretrainedConfig) -> PretrainedConfig:
     """Remap config attributes to match the expected names."""
     for old_attr, new_attr in _CONFIG_ATTRS_MAPPING.items():
         if hasattr(config, old_attr):
             if not hasattr(config, new_attr):
                 config.update({new_attr: getattr(config, old_attr)})
-            delattr(config, old_attr)
             logger.debug("Remapped config attribute '%s' to '%s'", old_attr,
                          new_attr)
     return config
@@ -415,15 +424,14 @@ def get_config(
             )
         else:
             try:
+                kwargs = _maybe_update_auto_config_kwargs(
+                    kwargs, model_type=model_type)
                 config = AutoConfig.from_pretrained(
                     model,
                     trust_remote_code=trust_remote_code,
                     revision=revision,
                     code_revision=code_revision,
                     token=_get_hf_token(),
-                    # some old custom model's config needs
-                    # `has_no_defaults_at_init=True` to work.
-                    has_no_defaults_at_init=trust_remote_code,
                     **kwargs,
                 )
             except ValueError as e: