Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

Xingyu-Zheng
/
Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM

Image-Text-to-Text
Safetensors
English
Chinese
qwen3_5
unsloth
qwen
qwen3.5
reasoning
chain-of-thought
Dense
vLLM
SGLang
conversational
4-bit precision
gptq
Model card Files Files and versions
xet
Community

Instructions to use Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Local Apps Settings
  • vLLM

    How to use Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM
  • SGLang

    How to use Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM 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 "Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM" \
        --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": "Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    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 "Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM" \
            --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": "Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
  • Unsloth Desktop
  • Docker Model Runner

    How to use Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM with Docker Model Runner:

    docker model run hf.co/Xingyu-Zheng/Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM
Qwen3.5-9B-GLM5.1-Distill-v1-INT4-FOEM
8.61 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
Xingyu-Zheng's picture
Xingyu-Zheng
Upload folder using huggingface_hub
13d0bf9 verified 5 months ago
  • .gitattributes
    1.57 kB
    Upload folder using huggingface_hub 5 months ago
  • README.md
    4.44 kB
    Update README.md 5 months ago
  • chat_template.jinja
    4.05 kB
    Upload folder using huggingface_hub 5 months ago
  • config.json
    4.44 kB
    Upload folder using huggingface_hub 5 months ago
  • generation_config.json
    230 Bytes
    Upload folder using huggingface_hub 5 months ago
  • model-00001-of-00003.safetensors
    2.96 GB
    xet
    Upload folder using huggingface_hub 5 months ago
  • model-00002-of-00003.safetensors
    4.29 GB
    xet
    Upload folder using huggingface_hub 5 months ago
  • model-00003-of-00003.safetensors
    1.34 GB
    xet
    Upload folder using huggingface_hub 5 months ago
  • model.safetensors.index.json
    128 kB
    Upload folder using huggingface_hub 5 months ago
  • processor_config.json
    1.3 kB
    Upload folder using huggingface_hub 5 months ago
  • quantize_config.json
    1.23 kB
    Upload folder using huggingface_hub 5 months ago
  • tokenizer.json
    20 MB
    xet
    Upload folder using huggingface_hub 5 months ago
  • tokenizer_config.json
    1.19 kB
    Upload folder using huggingface_hub 5 months ago