Text Generation
Safetensors
English
qwen2
gptqmodel
modelcloud
chat
qwq
instruct
int4
gptq
4bit
conversational
4-bit precision
Instructions to use ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1
- SGLang
How to use ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1 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 "ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1" \ --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": "ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1", "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 "ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1" \ --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": "ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1 with Docker Model Runner:
docker model run hf.co/ModelCloud/QwQ-32B-Preview-gptqmodel-4bit-vortex-v1
- Xet hash:
- 58c74a878a4716fffd364c5ca9eab7e4be25e2d3d51ebd56bc7864a4eed8e3f1
- Size of remote file:
- 282 MB
- SHA256:
- 7f241a7d02075688e89652c8e08918ce8589ae63153e89e1a01d65e100a5b010
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