base_url="http://localhost:8000/v1", api_key="key" # 如有必要,请替换为实际的API密钥 ) chat_completion = client.chat.completions.create( messages=[ { "role": "user", "content": "Tell about Bitcoin .", } ], model="Qwen/Qwen-7B-Chat", ) print(chat_completion.choices[0].message...
from openai import OpenAI model_id = "meta-llama/Meta-Llama-3-8B" # Modify OpenAI's API key and API base to use vLLM's API server. openai_api_key = "EMPTY" openai_api_base = "http://localhost:8000/v1" client = OpenAI( api_key=openai_api_key, base_url=openai_api_base, ) p...
运行vllm serve命令来启动Qwen/Qwen2-1.5B-Instruct服务,(1.5B参数的Qwen/Qwen2指令模型)自动设置数据类型(--dtype auto),并使用token-abc123作为API密钥进行认证(--api-key token-abc123)。 vllm的关键论点 --host HOSTNAME: 服务器主机名(默认:localhost) --port PORT: 服务器端口号(默认:8000) --api-...
为了查询服务器,我使用OpenAI的API框架,这可以完全兼容vllm的服务。 from openai import OpenAI model_id = "meta-llama/Meta-Llama-3-8B"# Modify OpenAI's API key and API base to use vLLM's API server.openai_api_key = "EMPTY"openai_api_...
例如,要在 2 个 GPU 上运行 API 服务器: python -m vllm.entrypoints.openai.api_server --model /root/autodl-tmp/Yi-6B-Chat --dtype auto --api-key token-agiclass --trust-remote-code --port 6006 --tensor-parallel-size 2 多卡调用一定是关键的能力,但是现在我还没有足够的动机来研究相关问题...
api_key=openai_api_key, base_url=openai_api_base, ) prompts = [ "### Human: Check if the numbers 8 and 1233 are powers of two.### Assistant:", "### Human: What is the division result of 75 divided by 1555?### Assistant:", ...
python -m vllm.entrypoints.openai.api_server --model /root/autodl-tmp/Yi-6B-Chat --dtype auto --api-key token-agiclass --trust-remote-code --port 6006 --tensor-parallel-size 2 1. 多卡调用一定是关键的能力,但是现在我还没有足够的动机来研究相关问题。
# Set OpenAI's API key and API base to use vLLM's API server. openai_api_key ="EMPTY" # 这里写内网IP和外网IP取决于你的连接环境 openai_api_base ="http://i-1.gpushare.com:30028/v1" client = OpenAI( api_key=openai_api_key, ...
openai_api_key = "EMPTY" openai_api_base = "http://120.48.131.39:8028/v1" client = OpenAI( api_key=openai_api_key, base_url=openai_api_base, ) chat_response = client.chat.completions.create( model="qwen", messages=[ {"role": "system", "content": "You are a helpful assistant....
OpenAI-compatible API server Support NVIDIA GPUs, AMD CPUs and GPUs, Intel CPUs and GPUs, PowerPC CPUs, TPU, and AWS Neuron. Prefix caching support Multi-lora support vLLM seamlessly supports most popular open-source models on HuggingFace, including: ...