gemma2-9b-instrunct how to use vllm?

[ArlanCooper]

i use vllm to support gemma2-9b-instruct to infer
i run this command:

python -m vllm.entrypoints.openai.api_server --served-model-name gemma-2-9b --model /data/gemma-2-9b-it

got this error:

INFO 07-16 16:31:06 selector.py:79] Using Flashinfer backend.
WARNING 07-16 16:31:06 selector.py:80] Flashinfer will be stuck on llama-2-7b, please avoid using Flashinfer as the backend when running on llama-2-7b.
INFO 07-16 16:31:07 selector.py:79] Using Flashinfer backend.
WARNING 07-16 16:31:07 selector.py:80] Flashinfer will be stuck on llama-2-7b, please avoid using Flashinfer as the backend when running on llama-2-7b.
INFO 07-16 16:31:11 model_runner.py:255] Loading model weights took 17.3781 GB
[rank0]: Traceback (most recent call last):
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/runpy.py", line 196, in _run_module_as_main
[rank0]:     return _run_code(code, main_globals, None,
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/runpy.py", line 86, in _run_code
[rank0]:     exec(code, run_globals)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/entrypoints/openai/api_server.py", line 216, in <module>
[rank0]:     engine = AsyncLLMEngine.from_engine_args(
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 431, in from_engine_args
[rank0]:     engine = cls(
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 360, in __init__
[rank0]:     self.engine = self._init_engine(*args, **kwargs)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 507, in _init_engine
[rank0]:     return engine_class(*args, **kwargs)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 256, in __init__
[rank0]:     self._initialize_kv_caches()
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 353, in _initialize_kv_caches
[rank0]:     self.model_executor.determine_num_available_blocks())
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 76, in determine_num_available_blocks
[rank0]:     return self.driver_worker.determine_num_available_blocks()
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/worker/worker.py", line 173, in determine_num_available_blocks
[rank0]:     self.model_runner.profile_run()
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 874, in profile_run
[rank0]:     self.execute_model(model_input, kv_caches, intermediate_tensors)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/home/powerop/work/conda/envs/qwen2/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 1201, in execute_model
[rank0]:     BatchDecodeWithPagedKVCacheWrapper(
[rank0]: TypeError: 'NoneType' object is not callable