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my-ai-stack
/
Stack-4.0-Qwen-3B-Merged

Text Generation
Transformers
Safetensors
English
qwen2
qwen2.5-coder
qwen2.5-coder-3b
code-generation
agentic-ai
tool-use
fine-tuned-llm
stack-4
stack-ai
sovereign-ai
enterprise
local-inference
3b-parameter-model
Eval Results (legacy)
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use my-ai-stack/Stack-4.0-Qwen-3B-Merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use my-ai-stack/Stack-4.0-Qwen-3B-Merged with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="my-ai-stack/Stack-4.0-Qwen-3B-Merged")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("my-ai-stack/Stack-4.0-Qwen-3B-Merged")
    model = AutoModelForCausalLM.from_pretrained("my-ai-stack/Stack-4.0-Qwen-3B-Merged")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use my-ai-stack/Stack-4.0-Qwen-3B-Merged with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "my-ai-stack/Stack-4.0-Qwen-3B-Merged"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "my-ai-stack/Stack-4.0-Qwen-3B-Merged",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/my-ai-stack/Stack-4.0-Qwen-3B-Merged
  • SGLang

    How to use my-ai-stack/Stack-4.0-Qwen-3B-Merged 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 "my-ai-stack/Stack-4.0-Qwen-3B-Merged" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "my-ai-stack/Stack-4.0-Qwen-3B-Merged",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    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 "my-ai-stack/Stack-4.0-Qwen-3B-Merged" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "my-ai-stack/Stack-4.0-Qwen-3B-Merged",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use my-ai-stack/Stack-4.0-Qwen-3B-Merged with Docker Model Runner:

    docker model run hf.co/my-ai-stack/Stack-4.0-Qwen-3B-Merged
Stack-4.0-Qwen-3B-Merged
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  • 1 contributor
History: 6 commits
Walid Sobhi
Upload benchmark_results.json with huggingface_hub
59689ba verified 13 days ago
  • .gitattributes
    1.52 kB
    initial commit 14 days ago
  • README.md
    6.21 kB
    Upload README.md with huggingface_hub 13 days ago
  • benchmark_results.json
    601 Bytes
    Upload benchmark_results.json with huggingface_hub 13 days ago
  • config.json
    1.55 kB
    Upload folder using huggingface_hub 14 days ago
  • generation_config.json
    242 Bytes
    Upload folder using huggingface_hub 14 days ago
  • model.safetensors
    6.17 GB
    xet
    Upload folder using huggingface_hub 14 days ago
  • readme.md
    2.36 kB
    Create readme.md 13 days ago