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Blockway
/
Agens-Volundr-32B-Preview

Text Generation
Transformers
Safetensors
English
Chinese
Yue Chinese
volundr
image-text-to-text
agens
blockway
agent
tool-use
code
long-context
linear-attention
sparse-attention
cantonese
conversational
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use Blockway/Agens-Volundr-32B-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Blockway/Agens-Volundr-32B-Preview with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Blockway/Agens-Volundr-32B-Preview", trust_remote_code=True)
    messages = [
        {
            "role": "user",
            "content": [
                {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
                {"type": "text", "text": "What animal is on the candy?"}
            ]
        },
    ]
    pipe(text=messages)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModelForImageTextToText
    model = AutoModelForImageTextToText.from_pretrained("Blockway/Agens-Volundr-32B-Preview", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Blockway/Agens-Volundr-32B-Preview with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Blockway/Agens-Volundr-32B-Preview"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Blockway/Agens-Volundr-32B-Preview",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/Blockway/Agens-Volundr-32B-Preview
  • SGLang

    How to use Blockway/Agens-Volundr-32B-Preview 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 "Blockway/Agens-Volundr-32B-Preview" \
        --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": "Blockway/Agens-Volundr-32B-Preview",
    		"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 "Blockway/Agens-Volundr-32B-Preview" \
            --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": "Blockway/Agens-Volundr-32B-Preview",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use Blockway/Agens-Volundr-32B-Preview with Docker Model Runner:

    docker model run hf.co/Blockway/Agens-Volundr-32B-Preview
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RTX PRO 6000 Blackwell 96GB (sm120) - serving recipe + head-to-head vs Qwen3.8-27B bf16, both with DFlash2

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#1 opened 6 days ago by
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