[Misc] Sort the list of embedding models (#10037)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/models/registry.py

@@ -94,33 +94,23 @@ _TEXT_GENERATION_MODELS = {
 _EMBEDDING_MODELS = {
     # [Text-only]
     "BertModel": ("bert", "BertEmbeddingModel"),
+    "DeciLMForCausalLM": ("decilm", "DeciLMForCausalLM"),
     "Gemma2Model": ("gemma2", "Gemma2EmbeddingModel"),
     "LlamaModel": ("llama", "LlamaEmbeddingModel"),
+    **{
+        # Multiple models share the same architecture, so we include them all
+        k: (mod, arch) for k, (mod, arch) in _TEXT_GENERATION_MODELS.items()
+        if arch == "LlamaForCausalLM"
+    },
     "MistralModel": ("llama", "LlamaEmbeddingModel"),
-    "Qwen2ForRewardModel": ("qwen2_rm", "Qwen2ForRewardModel"),
-    "Qwen2ForSequenceClassification": (
-        "qwen2_cls", "Qwen2ForSequenceClassification"),
-    "LlamaForCausalLM": ("llama", "LlamaForCausalLM"),
     "Phi3ForCausalLM": ("phi3", "Phi3ForCausalLM"),
-    "DeciLMForCausalLM": ("decilm", "DeciLMForCausalLM"),
+    "Qwen2ForRewardModel": ("qwen2_rm", "Qwen2ForRewardModel"),
+    "Qwen2ForSequenceClassification": ("qwen2_cls", "Qwen2ForSequenceClassification"),  # noqa: E501
     # [Multimodal]
     "LlavaNextForConditionalGeneration": ("llava_next", "LlavaNextForConditionalGeneration"),  # noqa: E501
     "Phi3VForCausalLM": ("phi3v", "Phi3VForCausalLM"),
 }
 
-def add_embedding_models(base_models, embedding_models):
-    with_pooler_method_models = {}
-    embedding_models_name = embedding_models.keys()
-    for name, (path, arch) in base_models.items():
-        if arch in embedding_models_name:
-            with_pooler_method_models[name] = (path, arch)
-    return with_pooler_method_models
-
-_EMBEDDING_MODELS = {
-    **add_embedding_models(_TEXT_GENERATION_MODELS, _EMBEDDING_MODELS),
-    **_EMBEDDING_MODELS,
-}
-
 _MULTIMODAL_MODELS = {
     # [Decoder-only]
     "Blip2ForConditionalGeneration": ("blip2", "Blip2ForConditionalGeneration"),