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ModelCloud
/
Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1

Text Generation
Safetensors
English
qwen2
gptqmodel
modelcloud
code
codeqwen
chat
qwen
qwen-coder
instruct
int4
gptq
4bit
conversational
4-bit precision
Model card Files Files and versions
xet
Community
4

Instructions to use ModelCloud/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/ModelCloud/Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1
  • SGLang

    How to use ModelCloud/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-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/Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use ModelCloud/Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1 with Docker Model Runner:

    docker model run hf.co/ModelCloud/Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1
Qwen2.5-Coder-32B-Instruct-gptqmodel-4bit-vortex-v1
21.2 GB
Ctrl+K
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  • 2 contributors
History: 3 commits
lrl-modelcloud's picture
lrl-modelcloud
6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0
8ad6f77 verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • config.json
    1.24 kB
    6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0 over 1 year ago
  • merges.txt
    1.67 MB
    6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0 over 1 year ago
  • model.safetensors
    21.2 GB
    xet
    f9689eb2e7de123ec5e6c9aaa375e040cc143a2c0c52ecdaf4b8412bb66519fc over 1 year ago
  • quantize_config.json
    385 Bytes
    6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0 over 1 year ago
  • tokenizer.json
    7.03 MB
    6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0 over 1 year ago
  • tokenizer_config.json
    7.31 kB
    6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0 over 1 year ago
  • vocab.json
    2.78 MB
    6ea60db1f8c653239860986e16ac0a2e9ab248e2df22f505175a724f16147fb0 over 1 year ago