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...
[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...
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 aGLM_API_KEYto run this code. Store it in a.envfile 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. ...
+ 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...
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...
Inference Acceleration: Supports inference acceleration engines like PyTorch, vLLM, LmDeploy, and provides OpenAI API for accelerating inference, deployment, and evaluation modules. Model Evaluation: Uses EvalScope as the evaluation backend and supports evaluation on 100+ datasets for both pure text and...
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...