Openai style api for open large language models, using LLMs just as chatgpt! Support for LLaMA, LLaMA-2, BLOOM, Falcon, Baichuan, Qwen, Xverse, SqlCoder, CodeLLaMA, ChatGLM, ChatGLM2, ChatGLM3 etc. 开源大模型的统一后端接口 - api-for-open-llm/tests/glm4v.
[rank0]: File "/root/ljm/ChatGLM4/GLM-4/api_server_vLLM/vllm-4v-request-test.py", line 95, in chat_print [rank0]: async for output in chat(): [rank0]: File "/root/ljm/ChatGLM4/GLM-4/api_server_vLLM/vllm-4v-request-test.py", line 90, in chat [rank0]: async for ou...
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Description optimize glm4v vision attention 1. Why the change? 2. User API changes 3. Summary of the change 4. How to test? N/A Unit test: Please manually trigger the PR Validation here by ...
You need a GLM_API_KEY to run this code. Store it in a .env file in the root directory of the project, or set them as environment variables. Since glm4v can't read local images, they need to be uploaded to a server first. Here, I've configured Tencent Cloud COS. If you are ru...
+ 自行构建服务端,并使用 `OpenAI API` 的请求格式与 GLM-4-9B-Chat 模型进行对话。本 demo 支持 Function Call 和 All Tools功能。 + 自行构建服务端,并使用 `OpenAI API` 的请求格式与 GLM-4-9B-Chat GLM-4v-9B 或者模型进行对话。本 demo 支持 Function Call 和 All Tools功能。 + 修改`open_...
GLM_API_KEY = os.getenv("GLM_API_KEY") cos_region = os.getenv('COS_REGION') cos_bucket_name = os.getenv('COS_BUCKET_NAME') secret_id = os.getenv('COS_SECRET_ID') secret_key = os.getenv('COS_SECRET_KEY') config = CosConfig(Region=cos_region, SecretId=secret_id, SecretKey=se...
but the Dify workflow node, it didn't get the glm4v response and return empty string. when I use gpt4o instead of the glm4v, it's works fine, but the glm4v server is compatiable OpenAI restful API, all of the interface and parameter is compatiable, so how to debug or resolve this...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...
The client uses the OpenAI API for invocation, for details refer to the LLM deployment documentation. Original model: CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat # 使用VLLM加速 CUDA_VISIBLE_DEVICES=0 swift deploy --model_type qwen1half-7b-chat \ --infer_backend vll...