Qwen

/

Qwen2-57B-A14B-Instruct-GPTQ-Int4

like 22

Follow

Qwen 7.46k

I have an error when run Qwen2-57B-A14B-Instruct-GPTQ-Int4 with vllm.

Command and Output:

(vllm) wish@wish-MS-7B92:/AIGC/Qwen$ CUDA_VISIBLE_DEVICES=1,2 python -m vllm.entrypoints.openai.api_server \
    --served-model-name Qwen2-57B-A14B-Instruct-GPTQ-Int4 \
    --model /AIGC/Qwen/hf/Qwen2-57B-A14B-Instruct-GPTQ-Int4
WARNING 06-07 16:41:21 config.py:213] gptq quantization is not fully optimized yet. The speed can be slower than non-quantized models.
INFO 06-07 16:41:21 llm_engine.py:161] Initializing an LLM engine (v0.4.3) with config: model='/AIGC/Qwen/hf/Qwen2-57B-A14B-Instruct-GPTQ-Int4', speculative_config=None, tokenizer='/AIGC/Qwen/hf/Qwen2-57B-A14B-Instruct-GPTQ-Int4', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, rope_scaling=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.float16, max_seq_len=32768, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=gptq, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), seed=0, served_model_name=Qwen2-57B-A14B-Instruct-GPTQ-Int4)
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
INFO 06-07 16:41:22 selector.py:120] Cannot use FlashAttention-2 backend for Volta and Turing GPUs.
INFO 06-07 16:41:22 selector.py:51] Using XFormers backend.
INFO 06-07 16:41:23 selector.py:120] Cannot use FlashAttention-2 backend for Volta and Turing GPUs.
INFO 06-07 16:41:23 selector.py:51] Using XFormers backend.
[rank0]: Traceback (most recent call last):
[rank0]:   File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
[rank0]:     return _run_code(code, main_globals, None,
[rank0]:   File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
[rank0]:     exec(code, run_globals)
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/entrypoints/openai/api_server.py", line 186, in <module>
[rank0]:     engine = AsyncLLMEngine.from_engine_args(
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 386, in from_engine_args
[rank0]:     engine = cls(
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 340, in __init__
[rank0]:     self.engine = self._init_engine(*args, **kwargs)
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 462, in _init_engine
[rank0]:     return engine_class(*args, **kwargs)
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 222, in __init__
[rank0]:     self.model_executor = executor_class(
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/executor/executor_base.py", line 41, in __init__
[rank0]:     self._init_executor()
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 24, in _init_executor
[rank0]:     self.driver_worker.load_model()
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/worker/worker.py", line 121, in load_model
[rank0]:     self.model_runner.load_model()
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 134, in load_model
[rank0]:     self.model = get_model(
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/__init__.py", line 21, in get_model
[rank0]:     return loader.load_model(model_config=model_config,
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/loader.py", line 240, in load_model
[rank0]:     model = _initialize_model(model_config, self.load_config,
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/model_loader/loader.py", line 91, in _initialize_model
[rank0]:     return model_class(config=model_config.hf_config,
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/models/qwen2_moe.py", line 389, in __init__
[rank0]:     self.model = Qwen2MoeModel(config, cache_config, quant_config)
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/models/qwen2_moe.py", line 349, in __init__
[rank0]:     self.layers = nn.ModuleList([
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/models/qwen2_moe.py", line 350, in <listcomp>
[rank0]:     Qwen2MoeDecoderLayer(config,
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/models/qwen2_moe.py", line 290, in __init__
[rank0]:     self.mlp = Qwen2MoeSparseMoeBlock(config=config,
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/models/qwen2_moe.py", line 114, in __init__
[rank0]:     self.pack_params()
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/vllm/model_executor/models/qwen2_moe.py", line 138, in pack_params
[rank0]:     w1.append(expert.gate_up_proj.weight)
[rank0]:   File "/AIGC/venvs/vllm/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1709, in __getattr__
[rank0]:     raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
[rank0]: AttributeError: 'MergedColumnParallelLinear' object has no attribute 'weight'. Did you mean: 'qweight'?

This seems to be a problem with the code.