add qwen3

vllm-v0.6.2/tests/lora/test_lora_huggingface.py

@@ -0,0 +1,39 @@
+from typing import List
+
+import pytest
+
+from vllm.lora.models import LoRAModel
+from vllm.lora.utils import get_adapter_absolute_path
+from vllm.model_executor.models.llama import LlamaForCausalLM
+
+# Provide absolute path and huggingface lora ids
+lora_fixture_name = ["sql_lora_files", "sql_lora_huggingface_id"]
+
+
+@pytest.mark.parametrize("lora_fixture_name", lora_fixture_name)
+def test_load_checkpoints_from_huggingface(lora_fixture_name, request):
+    lora_name = request.getfixturevalue(lora_fixture_name)
+    supported_lora_modules = LlamaForCausalLM.supported_lora_modules
+    packed_modules_mapping = LlamaForCausalLM.packed_modules_mapping
+    embedding_modules = LlamaForCausalLM.embedding_modules
+    embed_padding_modules = LlamaForCausalLM.embedding_padding_modules
+    expected_lora_modules: List[str] = []
+    for module in supported_lora_modules:
+        if module in packed_modules_mapping:
+            expected_lora_modules.extend(packed_modules_mapping[module])
+        else:
+            expected_lora_modules.append(module)
+
+    lora_path = get_adapter_absolute_path(lora_name)
+
+    # lora loading should work for either absolute path and hugggingface id.
+    lora_model = LoRAModel.from_local_checkpoint(
+        lora_path,
+        expected_lora_modules,
+        lora_model_id=1,
+        device="cpu",
+        embedding_modules=embedding_modules,
+        embedding_padding_modules=embed_padding_modules)
+
+    # Assertions to ensure the model is loaded correctly
+    assert lora_model is not None, "LoRAModel is not loaded correctly"