Instructions to use QuantTrio/GLM-4.1V-9B-Thinking-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use QuantTrio/GLM-4.1V-9B-Thinking-AWQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "QuantTrio/GLM-4.1V-9B-Thinking-AWQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuantTrio/GLM-4.1V-9B-Thinking-AWQ", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/QuantTrio/GLM-4.1V-9B-Thinking-AWQ
- SGLang
How to use QuantTrio/GLM-4.1V-9B-Thinking-AWQ with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "QuantTrio/GLM-4.1V-9B-Thinking-AWQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuantTrio/GLM-4.1V-9B-Thinking-AWQ", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "QuantTrio/GLM-4.1V-9B-Thinking-AWQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "QuantTrio/GLM-4.1V-9B-Thinking-AWQ", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use QuantTrio/GLM-4.1V-9B-Thinking-AWQ with Docker Model Runner:
docker model run hf.co/QuantTrio/GLM-4.1V-9B-Thinking-AWQ
File size: 364 Bytes
e37d336 | 1 2 3 4 5 6 7 8 9 10 11 | {
"size": {"shortest_edge": 12544, "longest_edge": 9633792},
"do_rescale": true,
"patch_size": 14,
"temporal_patch_size": 2,
"merge_size": 2,
"image_mean": [0.48145466, 0.4578275, 0.40821073],
"image_std": [0.26862954, 0.26130258, 0.27577711],
"image_processor_type": "Glm4vImageProcessor",
"processor_class": "Glm4vProcessor"
} |