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xun
/
Qwen-Audio-Chat-Int4

Text Generation
Transformers
PyTorch
Chinese
English
qwen
multimodal
音频理解
custom_code
4-bit precision
gptq
Model card Files Files and versions
xet
Community
1

Instructions to use xun/Qwen-Audio-Chat-Int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use xun/Qwen-Audio-Chat-Int4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="xun/Qwen-Audio-Chat-Int4", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("xun/Qwen-Audio-Chat-Int4", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use xun/Qwen-Audio-Chat-Int4 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "xun/Qwen-Audio-Chat-Int4"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "xun/Qwen-Audio-Chat-Int4",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/xun/Qwen-Audio-Chat-Int4
  • SGLang

    How to use xun/Qwen-Audio-Chat-Int4 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 "xun/Qwen-Audio-Chat-Int4" \
        --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": "xun/Qwen-Audio-Chat-Int4",
    		"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 "xun/Qwen-Audio-Chat-Int4" \
            --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": "xun/Qwen-Audio-Chat-Int4",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use xun/Qwen-Audio-Chat-Int4 with Docker Model Runner:

    docker model run hf.co/xun/Qwen-Audio-Chat-Int4
Qwen-Audio-Chat-Int4
7.21 GB
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  • 1 contributor
History: 2 commits
xun's picture
xun
init
8bf83e9 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • LICENSE
    6.9 kB
    init over 2 years ago
  • README.md
    7.98 kB
    init over 2 years ago
  • audio.py
    15 kB
    init over 2 years ago
  • config.json
    1.43 kB
    init over 2 years ago
  • configuration.json
    78 Bytes
    init over 2 years ago
  • configuration_qwen.py
    2.35 kB
    init over 2 years ago
  • cpp_kernels.py
    1.92 kB
    init over 2 years ago
  • generation_config.json
    221 Bytes
    init over 2 years ago
  • mel_filters.npz

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    2.05 kB
    xet
    init over 2 years ago
  • modeling_qwen.py
    58.3 kB
    init over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (5)

    • "torch.HalfStorage",
    • "torch.BFloat16Storage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.IntStorage"

    What is a pickle import?

    7.21 GB
    xet
    init over 2 years ago
  • quantize_config.json
    211 Bytes
    init over 2 years ago
  • qwen.tiktoken
    2.56 MB
    init over 2 years ago
  • qwen_generation_utils.py
    15.4 kB
    init over 2 years ago
  • special_tokens_map.json
    3 Bytes
    init over 2 years ago
  • tokenization_qwen.py
    22.8 kB
    init over 2 years ago
  • tokenizer_config.json
    211 Bytes
    init over 2 years ago