embedding 模型 使用通用文本向量 text-embedding-v1 from dotenv import load_dotenv import os load_dotenv() os.environ['DASHSCOPE_API_KEY'] = os.getenv('DASHSCOPE_API_KEY') os.environ['DASHSCOPE_BASE_URL'] = os.getenv('DASHSCOPE_BASE_URL') import dashscope from http import HTTPStatus imp...
#"embed_model": "text-embedding-v1" # embedding 模型名称 }, # 百川 API,申请方式请参考 https://www.baichuan-ai.com/home#api-enter "baichuan-api": { "version": "Baichuan2-53B", "api_key": "", "secret_key": "", "provider": "BaiChuanWorker", }, # Azure API "azure-api": {...
api_base = "http://localhost:8000/v1" openai.api_key = "none" # create a request activating streaming response for chunk in openai.ChatCompletion.create( model="Qwen", messages=[ {"role": "user", "content": "你好"} ], stream=True # Specifying stop words in streaming output format ...
By using strong LLMs as judges and converting multimodal information into text. 2023.8.31 🌟🌟🌟 We release the Int4 quantized model for Qwen-VL-Chat, Qwen-VL-Chat-Int4, which requires low memory costs but achieves improved inference speed. Besides, there is no significant performance ...
('DASHSCOPE_API_KEY'), base_url="https://dashscope.aliyuncs.com/compatible-mode/v1", ) completion = client.chat.completions.create( model="qwen-vl-max-latest", messages=[ {"role":"system","content": [{"type":"text","text":"You are a helpful assistant."}]}, {"role":"user",...
('DASHSCOPE_API_KEY'), base_url="https://dashscope.aliyuncs.com/compatible-mode/v1", ) completion = client.chat.completions.create( model="qwen-vl-max-latest", messages=[ {"role":"system","content": [{"type":"text","text":"You are a helpful assistant."}]}, {"role":"user",...
1年前 finetune Update finetune_ds.sh 1年前 touchstone add korean documents (#169) 1年前 .gitignore add docker support (#75) 1年前 BUILD.md add docker support (#75) 1年前 Dockerfile.qwendemo add docker support (#75) 1年前
1年前 Dockerfile.qwendemo add docker support (#75) 1年前 Dockerfile.qwenint4openai add docker support (#75) 1年前 Dockerfile.qwenopenai add docker support (#75) 1年前 FAQ.md Initial commit 1年前 FAQ_ja.md Add Japanese FAQ 1年前 ...
下面记录7B和14B模型在单GPU使用LoRA(LoRA (emb)指的是embedding和输出层参与训练,而LoRA则不优化这部分参数)和QLoRA时处理不同长度输入的显存占用和训练速度的情况。本次评测运行于单张A100-SXM4-80G GPU,使用CUDA 11.8和Pytorch 2.0,并使用了flash attention 2。我们统一使用batch size为1,gradient accumulation为...
定义app的路由:路由指向v1/chat/completions 定义app的处理函数:处理函数调用generate_text函数,传入request接收的兼容OpenAI的请求体模型。 文本和图像生成generate_text:提取query、image_url,构造query,传入qwen_vl.chat(),基于图片和文本生成response返回