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summerMC
/
Qwen3.5-2B-SpeedX

Text Generation
Transformers
Safetensors
qwen3_5_gdn24
qwen
qwen3.5
recurrent
rnn
gated-delta-net
gdn
custom_code
cuda-graph
fp8
experimental
conversational
Model card Files Files and versions
xet
Community

Instructions to use summerMC/Qwen3.5-2B-SpeedX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use summerMC/Qwen3.5-2B-SpeedX with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="summerMC/Qwen3.5-2B-SpeedX", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("summerMC/Qwen3.5-2B-SpeedX", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use summerMC/Qwen3.5-2B-SpeedX with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "summerMC/Qwen3.5-2B-SpeedX"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "summerMC/Qwen3.5-2B-SpeedX",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/summerMC/Qwen3.5-2B-SpeedX
  • SGLang

    How to use summerMC/Qwen3.5-2B-SpeedX 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 "summerMC/Qwen3.5-2B-SpeedX" \
        --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": "summerMC/Qwen3.5-2B-SpeedX",
    		"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 "summerMC/Qwen3.5-2B-SpeedX" \
            --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": "summerMC/Qwen3.5-2B-SpeedX",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use summerMC/Qwen3.5-2B-SpeedX with Docker Model Runner:

    docker model run hf.co/summerMC/Qwen3.5-2B-SpeedX
Qwen3.5-2B-SpeedX
3.86 GB
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  • 1 contributor
History: 10 commits
summerMC's picture
summerMC
Update fused_ops.py
b1a8f82 verified about 10 hours ago
  • .gitattributes
    1.68 kB
    Rename Qwen3.5-2B-BF16.gguf to Qwen3.5-2B-4bit.gguf 1 day ago
  • README.md
    6.67 kB
    Upload README.md 1 day ago
  • chat_template.jinja
    7.76 kB
    Upload tokenizer 1 day ago
  • config.json
    2.71 kB
    Upload Qwen35GDN24ForCausalLM 1 day ago
  • configuration_qwen35_gdn24.py
    2.56 kB
    Upload Qwen35GDN24ForCausalLM 1 day ago
  • fused_ops.py
    15.1 kB
    Update fused_ops.py about 10 hours ago
  • generation_config.json
    184 Bytes
    Upload Qwen35GDN24ForCausalLM 1 day ago
  • model.safetensors
    3.84 GB
    xet
    Upload Qwen35GDN24ForCausalLM 1 day ago
  • modeling_qwen35_gdn24.py
    13 kB
    Upload Qwen35GDN24ForCausalLM 1 day ago
  • tokenizer.json
    20 MB
    xet
    Upload tokenizer 1 day ago
  • tokenizer_config.json
    1.23 kB
    Upload tokenizer 1 day ago