[Usage]: Error while serving nomic-embed-v1 in vllm docker #20129
Description
Your current environment
The output of `python collect_env.py` -
Cannot run the code
OS: Ubuntu 22.04.5 LTS
CUDA Driver Version: 535.230.02
CUDA Version: 12.2
GPU Configuration: NVIDIA L40S 48GB
I am trying to serve nomic-embed-v1 and v1.5 embedding models through vllm docker, using the following command -
docker run --name nomic_inf -d --rm --runtime nvidia --gpus device=0 -v /var/models:/var/models -p 8070:8000 --ipc=host vllm/vllm-openai:latest --model /var/models/nomic-embed-text-v1.5 --served-model-name nomic-embed-text --task=embed --trust-remote-code
But I am getting the following error -
INFO 06-26 06:53:05 [__init__.py:239] Automatically detected platform cuda.
INFO 06-26 06:53:07 [api_server.py:1034] vLLM API server version 0.8.4
INFO 06-26 06:53:07 [api_server.py:1035] args: Namespace(host=None, port=8000, uvicorn_log_level='info', disable_uvicorn_access_log=False, allow_credentials=False, allowed_origins=['*'], allowed_methods=['*'], allowed_headers=['*'], api_key=None, lora_modules=None, prompt_adapters=None, chat_template=None, chat_template_content_format='auto', response_role='assistant', ssl_keyfile=None, ssl_certfile=None, ssl_ca_certs=None, enable_ssl_refresh=False, ssl_cert_reqs=0, root_path=None, middleware=[], return_tokens_as_token_ids=False, disable_frontend_multiprocessing=False, enable_request_id_headers=False, enable_auto_tool_choice=False, tool_call_parser=None, tool_parser_plugin='', model='/var/models/nomic-embed-text-v1.5', task='embed', tokenizer=None, hf_config_path=None, skip_tokenizer_init=False, revision=None, code_revision=None, tokenizer_revision=None, tokenizer_mode='auto', trust_remote_code=True, allowed_local_media_path=None, load_format='auto', download_dir=None, model_loader_extra_config=None, use_tqdm_on_load=True, config_format=<ConfigFormat.AUTO: 'auto'>, dtype='auto', kv_cache_dtype='auto', max_model_len=None, guided_decoding_backend='auto', logits_processor_pattern=None, model_impl='auto', distributed_executor_backend=None, pipeline_parallel_size=1, tensor_parallel_size=1, data_parallel_size=1, enable_expert_parallel=False, max_parallel_loading_workers=None, ray_workers_use_nsight=False, disable_custom_all_reduce=False, block_size=None, enable_prefix_caching=None, prefix_caching_hash_algo='builtin', disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=None, swap_space=4, cpu_offload_gb=0, gpu_memory_utilization=0.9, num_gpu_blocks_override=None, max_num_batched_tokens=None, max_num_partial_prefills=1, max_long_partial_prefills=1, long_prefill_token_threshold=0, max_num_seqs=None, max_logprobs=20, disable_log_stats=False, quantization=None, rope_scaling=None, rope_theta=None, hf_token=None, hf_overrides=None, enforce_eager=False, max_seq_len_to_capture=8192, tokenizer_pool_size=0, tokenizer_pool_type='ray', tokenizer_pool_extra_config=None, limit_mm_per_prompt=None, mm_processor_kwargs=None, disable_mm_preprocessor_cache=False, enable_lora=False, enable_lora_bias=False, max_loras=1, max_lora_rank=16, lora_extra_vocab_size=256, lora_dtype='auto', long_lora_scaling_factors=None, max_cpu_loras=None, fully_sharded_loras=False, enable_prompt_adapter=False, max_prompt_adapters=1, max_prompt_adapter_token=0, device='auto', num_scheduler_steps=1, multi_step_stream_outputs=True, scheduler_delay_factor=0.0, enable_chunked_prefill=None, speculative_config=None, ignore_patterns=[], preemption_mode=None, served_model_name=['nomic-embed-text'], qlora_adapter_name_or_path=None, show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, disable_async_output_proc=False, scheduling_policy='fcfs', scheduler_cls='vllm.core.scheduler.Scheduler', override_neuron_config=None, override_pooler_config=None, compilation_config=None, kv_transfer_config=None, worker_cls='auto', worker_extension_cls='', generation_config='auto', override_generation_config=None, enable_sleep_mode=False, calculate_kv_scales=False, additional_config=None, enable_reasoning=False, reasoning_parser=None, disable_cascade_attn=False, disable_chunked_mm_input=False, disable_log_requests=False, max_log_len=None, disable_fastapi_docs=False, enable_prompt_tokens_details=False, enable_server_load_tracking=False)
A new version of the following files was downloaded from https://huggingface.co/nomic-ai/nomic-bert-2048:
- configuration_hf_nomic_bert.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
INFO 06-26 06:53:07 [config.py:553] Found sentence-transformers tokenize configuration.
INFO 06-26 06:53:07 [config.py:2832] Downcasting torch.float32 to torch.float16.
INFO 06-26 06:53:13 [config.py:449] Found sentence-transformers modules configuration.
INFO 06-26 06:53:13 [config.py:469] Found pooling configuration.
WARNING 06-26 06:53:13 [arg_utils.py:1731] --task embed is not supported by the V1 Engine. Falling back to V0.
INFO 06-26 06:53:13 [api_server.py:246] Started engine process with PID 221
INFO 06-26 06:53:15 [__init__.py:239] Automatically detected platform cuda.
INFO 06-26 06:53:16 [llm_engine.py:243] Initializing a V0 LLM engine (v0.8.4) with config: model='/var/models/nomic-embed-text-v1.5', speculative_config=None, tokenizer='/var/models/nomic-embed-text-v1.5', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.float16, max_seq_len=8192, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='auto', reasoning_backend=None), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=nomic-embed-text, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=None, chunked_prefill_enabled=False, use_async_output_proc=False, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=PoolerConfig(pooling_type='MEAN', normalize=False, softmax=None, step_tag_id=None, returned_token_ids=None), compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":256}, use_cached_outputs=True,
INFO 06-26 06:53:17 [cuda.py:292] Using Flash Attention backend.
INFO 06-26 06:53:17 [parallel_state.py:959] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, TP rank 0
INFO 06-26 06:53:17 [model_runner.py:1110] Starting to load model /var/models/nomic-embed-text-v1.5...
A new version of the following files was downloaded from https://huggingface.co/nomic-ai/nomic-bert-2048:
- modeling_hf_nomic_bert.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
Process SpawnProcess-1:
ERROR 06-26 06:53:18 [engine.py:448] NomicBertModel has no vLLM implementation and the Transformers implementation is not compatible with vLLM. Try setting VLLM_USE_V1=0.
ERROR 06-26 06:53:18 [engine.py:448] Traceback (most recent call last):
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 436, in run_mp_engine
ERROR 06-26 06:53:18 [engine.py:448] engine = MQLLMEngine.from_vllm_config(
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 128, in from_vllm_config
ERROR 06-26 06:53:18 [engine.py:448] return cls(
ERROR 06-26 06:53:18 [engine.py:448] ^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 82, in __init__
ERROR 06-26 06:53:18 [engine.py:448] self.engine = LLMEngine(*args, **kwargs)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/engine/llm_engine.py", line 282, in __init__
ERROR 06-26 06:53:18 [engine.py:448] self.model_executor = executor_class(vllm_config=vllm_config, )
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/executor_base.py", line 52, in __init__
ERROR 06-26 06:53:18 [engine.py:448] self._init_executor()
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/uniproc_executor.py", line 47, in _init_executor
ERROR 06-26 06:53:18 [engine.py:448] self.collective_rpc("load_model")
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/executor/uniproc_executor.py", line 56, in collective_rpc
ERROR 06-26 06:53:18 [engine.py:448] answer = run_method(self.driver_worker, method, args, kwargs)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/utils.py", line 2378, in run_method
ERROR 06-26 06:53:18 [engine.py:448] return func(*args, **kwargs)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/worker/worker.py", line 183, in load_model
ERROR 06-26 06:53:18 [engine.py:448] self.model_runner.load_model()
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/worker/model_runner.py", line 1113, in load_model
ERROR 06-26 06:53:18 [engine.py:448] self.model = get_model(vllm_config=self.vllm_config)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/__init__.py", line 14, in get_model
ERROR 06-26 06:53:18 [engine.py:448] return loader.load_model(vllm_config=vllm_config)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/loader.py", line 452, in load_model
ERROR 06-26 06:53:18 [engine.py:448] model = _initialize_model(vllm_config=vllm_config)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/loader.py", line 123, in _initialize_model
ERROR 06-26 06:53:18 [engine.py:448] model_class, _ = get_model_architecture(model_config)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/utils.py", line 104, in get_model_architecture
ERROR 06-26 06:53:18 [engine.py:448] architectures = resolve_transformers_arch(model_config, architectures)
ERROR 06-26 06:53:18 [engine.py:448] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ERROR 06-26 06:53:18 [engine.py:448] File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/utils.py", line 72, in resolve_transformers_arch
ERROR 06-26 06:53:18 [engine.py:448] raise ValueError(
ERROR 06-26 06:53:18 [engine.py:448] ValueError: NomicBertModel has no vLLM implementation and the Transformers implementation is not compatible with vLLM. Try setting VLLM_USE_V1=0.
Traceback (most recent call last):
File "/usr/lib/python3.12/multiprocessing/process.py", line 314, in _bootstrap
self.run()
File "/usr/lib/python3.12/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 450, in run_mp_engine
raise e
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 436, in run_mp_engine
engine = MQLLMEngine.from_vllm_config(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 128, in from_vllm_config
return cls(
^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/multiprocessing/engine.py", line 82, in __init__
self.engine = LLMEngine(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/engine/llm_engine.py", line 282, in __init__
self.model_executor = executor_class(vllm_config=vllm_config, )
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/executor_base.py", line 52, in __init__
self._init_executor()
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/uniproc_executor.py", line 47, in _init_executor
self.collective_rpc("load_model")
File "/usr/local/lib/python3.12/dist-packages/vllm/executor/uniproc_executor.py", line 56, in collective_rpc
answer = run_method(self.driver_worker, method, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/utils.py", line 2378, in run_method
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/worker/worker.py", line 183, in load_model
self.model_runner.load_model()
File "/usr/local/lib/python3.12/dist-packages/vllm/worker/model_runner.py", line 1113, in load_model
self.model = get_model(vllm_config=self.vllm_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/__init__.py", line 14, in get_model
return loader.load_model(vllm_config=vllm_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/loader.py", line 452, in load_model
model = _initialize_model(vllm_config=vllm_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/loader.py", line 123, in _initialize_model
model_class, _ = get_model_architecture(model_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/utils.py", line 104, in get_model_architecture
architectures = resolve_transformers_arch(model_config, architectures)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/model_executor/model_loader/utils.py", line 72, in resolve_transformers_arch
raise ValueError(
ValueError: NomicBertModel has no vLLM implementation and the Transformers implementation is not compatible with vLLM. Try setting VLLM_USE_V1=0.
[rank0]:[W626 06:53:18.776894509 ProcessGroupNCCL.cpp:1496] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator())
Traceback (most recent call last):
File "<frozen runpy>", line 198, in _run_module_as_main
File "<frozen runpy>", line 88, in _run_code
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 1121, in <module>
uvloop.run(run_server(args))
File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 109, in run
return __asyncio.run(
^^^^^^^^^^^^^^
File "/usr/lib/python3.12/asyncio/runners.py", line 195, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "uvloop/loop.pyx", line 1518, in uvloop.loop.Loop.run_until_complete
File "/usr/local/lib/python3.12/dist-packages/uvloop/__init__.py", line 61, in wrapper
return await main
^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 1069, in run_server
async with build_async_engine_client(args) as engine_client:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 146, in build_async_engine_client
async with build_async_engine_client_from_engine_args(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
return await anext(self.gen)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/vllm/entrypoints/openai/api_server.py", line 269, in build_async_engine_client_from_engine_args
raise RuntimeError(
RuntimeError: Engine process failed to start. See stack trace for the root cause.
How would you like to use vllm
I want to run inference of a [specific model](put link here). I don't know how to integrate it with vllm.
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