Add model builder for Qwen2_5_VLTextModel

src/python/py/models/builder.py

@@ -36,6 +36,7 @@
     Phi4MMModel,
     PhiModel,
     Qwen3Model,
+    Qwen25VLTextModel,
     QwenModel,
     SmolLM3Model,
 )
@@ -160,7 +161,15 @@ def set_onnx_dtype(precision: str, extra_options: dict[str, Any]) -> ir.DataType
 
 
 @torch.no_grad
-def create_model(model_name, input_path, output_dir, precision, execution_provider, cache_dir, **extra_options):
+def create_model(
+    model_name,
+    input_path,
+    output_dir,
+    precision,
+    execution_provider,
+    cache_dir,
+    **extra_options,
+):
     if execution_provider == "NvTensorRtRtx":
         execution_provider = "trt-rtx"
         extra_options["use_qdq"] = True
@@ -180,7 +189,10 @@ def create_model(model_name, input_path, output_dir, precision, execution_provid
         from peft import PeftConfig
 
         peft_config = PeftConfig.from_pretrained(
-            extra_options["adapter_path"], token=hf_token, trust_remote_code=hf_remote, **extra_kwargs
+            extra_options["adapter_path"],
+            token=hf_token,
+            trust_remote_code=hf_remote,
+            **extra_kwargs,
         )
         config.update(peft_config.__dict__)
 
@@ -291,6 +303,16 @@ def create_model(model_name, input_path, output_dir, precision, execution_provid
         onnx_model = Qwen3Model(config, io_dtype, onnx_dtype, execution_provider, cache_dir, extra_options)
     elif config.architectures[0] == "SmolLM3ForCausalLM":
         onnx_model = SmolLM3Model(config, io_dtype, onnx_dtype, execution_provider, cache_dir, extra_options)
+    elif config.architectures[0] == "Qwen2_5_VLForConditionalGeneration":
+        text_config = config.text_config
+        for key in text_config:
+            if not hasattr(config, key):
+                setattr(config, key, getattr(text_config, key))
+        print(
+            "WARNING: This is only generating the text component of the model. Setting `--extra_options exclude_embeds=true` by default."
+        )
+        extra_options["exclude_embeds"] = True
+        onnx_model = Qwen25VLTextModel(config, io_dtype, onnx_dtype, execution_provider, cache_dir, extra_options)
     elif config_only:
         # Create base Model class to guess model attributes
         onnx_model = Model(config, io_dtype, onnx_dtype, execution_provider, cache_dir, extra_options)

src/python/py/models/builders/__init__.py

@@ -23,7 +23,7 @@
     Phi4MMModel,
     PhiModel,
 )
-from .qwen import Qwen3Model, QwenModel
+from .qwen import Qwen3Model, Qwen25VLTextModel, QwenModel
 from .smollm import SmolLM3Model
 
 __all__ = [
@@ -48,6 +48,7 @@
     "Phi4MMModel",
     "PhiModel",
     "Qwen3Model",
+    "Qwen25VLTextModel",
     "QwenModel",
     "SmolLM3Model",
 ]