run qwen-1.5-4b-chat with vllm worker failed: max seq len (32768) is larger than the maximum number of tokens

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Error logs:
```shell
Run model worker...
INFO 03-20 19:18:21 llm_engine.py:72] Initializing an LLM engine with config: model='/data/models/qwen1.5-4b-chat', tokenizer='/data/models/qwen1.5-4b-chat', tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=True, kv_cache_dtype=auto, seed=0)
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
INFO 03-20 19:18:27 llm_engine.py:322] # GPU blocks: 1842, # CPU blocks: 655
2024-03-20 19:18:27 | ERROR | stderr | Traceback (most recent call last):
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/lib/python3.9/runpy.py", line 197, in _run_module_as_main
2024-03-20 19:18:27 | ERROR | stderr | return _run_code(code, main_globals, None,
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/lib/python3.9/runpy.py", line 87, in _run_code
2024-03-20 19:18:27 | ERROR | stderr | exec(code, run_globals)
2024-03-20 19:18:27 | ERROR | stderr | File "/FastChat/fastchat/serve/vllm_worker.py", line 290, in
2024-03-20 19:18:27 | ERROR | stderr | engine = AsyncLLMEngine.from_engine_args(engine_args)
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/vllm/engine/async_llm_engine.py", line 623, in from_engine_args
2024-03-20 19:18:27 | ERROR | stderr | engine = cls(parallel_config.worker_use_ray,
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/vllm/engine/async_llm_engine.py", line 319, in __init__
2024-03-20 19:18:27 | ERROR | stderr | self.engine = self._init_engine(*args, **kwargs)
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/vllm/engine/async_llm_engine.py", line 364, in _init_engine
2024-03-20 19:18:27 | ERROR | stderr | return engine_class(*args, **kwargs)
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/vllm/engine/llm_engine.py", line 114, in __init__
2024-03-20 19:18:27 | ERROR | stderr | self._init_cache()
2024-03-20 19:18:27 | ERROR | stderr | File "/usr/local/lib/python3.9/dist-packages/vllm/engine/llm_engine.py", line 331, in _init_cache
2024-03-20 19:18:27 | ERROR | stderr | raise ValueError(
2024-03-20 19:18:27 | ERROR | stderr | ValueError: The model's max seq len (32768) is larger than the maximum number of tokens that can be stored in KV cache (29472). Try increasing `gpu_memory_utilization` or decreasing `max_model_len` when initializing the engine.
```

Here I can find dicussion about vllm:
https://github.com/vllm-project/vllm/issues/2418

Start with fastchat/serve/vllm_worker.py around the AsyncLLMEngine initialization shown in the traceback, then compare the Qwen model's sequence length with vLLM's KV-cache capacity. Reproduce the failure using the reported qwen-1.5-4b-chat configuration and determine what behavior or configuration change should prevent the worker from exiting.

Written by the indexing model from the issue text.