Instructions to use GSJL/QwQ-32B-GPTQ_4bit-128g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use GSJL/QwQ-32B-GPTQ_4bit-128g with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GSJL/QwQ-32B-GPTQ_4bit-128g" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GSJL/QwQ-32B-GPTQ_4bit-128g", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/GSJL/QwQ-32B-GPTQ_4bit-128g
- SGLang
How to use GSJL/QwQ-32B-GPTQ_4bit-128g 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 "GSJL/QwQ-32B-GPTQ_4bit-128g" \ --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": "GSJL/QwQ-32B-GPTQ_4bit-128g", "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 "GSJL/QwQ-32B-GPTQ_4bit-128g" \ --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": "GSJL/QwQ-32B-GPTQ_4bit-128g", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use GSJL/QwQ-32B-GPTQ_4bit-128g with Docker Model Runner:
docker model run hf.co/GSJL/QwQ-32B-GPTQ_4bit-128g
- Xet hash:
- 15499d2dd342acd85bcc115f3554cd7e5c1372390942e3f7a4ead9ec975d8ca3
- Size of remote file:
- 3.48 GB
- SHA256:
- 813942929cfc754b44e44115881f7fa71451153bfbe3bb45b66240a63abeffa0
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