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model-scope
/
glm-4-9b-chat-GPTQ-Int4

Text Generation
Transformers
Safetensors
chatglm
feature-extraction
gptq
int4
量化修复
vLLM
custom_code
4-bit precision
Model card Files Files and versions
xet
Community
1

Instructions to use model-scope/glm-4-9b-chat-GPTQ-Int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use model-scope/glm-4-9b-chat-GPTQ-Int4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="model-scope/glm-4-9b-chat-GPTQ-Int4", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("model-scope/glm-4-9b-chat-GPTQ-Int4", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use model-scope/glm-4-9b-chat-GPTQ-Int4 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "model-scope/glm-4-9b-chat-GPTQ-Int4"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "model-scope/glm-4-9b-chat-GPTQ-Int4",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/model-scope/glm-4-9b-chat-GPTQ-Int4
  • SGLang

    How to use model-scope/glm-4-9b-chat-GPTQ-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 "model-scope/glm-4-9b-chat-GPTQ-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": "model-scope/glm-4-9b-chat-GPTQ-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 "model-scope/glm-4-9b-chat-GPTQ-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": "model-scope/glm-4-9b-chat-GPTQ-Int4",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use model-scope/glm-4-9b-chat-GPTQ-Int4 with Docker Model Runner:

    docker model run hf.co/model-scope/glm-4-9b-chat-GPTQ-Int4
glm-4-9b-chat-GPTQ-Int4
6.89 GB
Ctrl+K
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  • 2 contributors
History: 13 commits
modelscope
fix license verification
126fa11 almost 2 years ago
  • .gitattributes
    1.64 kB
    System init .gitattributes almost 2 years ago
  • README.md
    2.81 kB
    fix license verification almost 2 years ago
  • added_tokens.json
    356 Bytes
    'upload model' almost 2 years ago
  • config.json
    2.1 kB
    '优化模型量化损失' almost 2 years ago
  • configuration.json
    57 Bytes
    'upload model' almost 2 years ago
  • configuration_chatglm.py
    2.27 kB
    'upload model' almost 2 years ago
  • generation_config.json
    129 Bytes
    '优化模型量化损失' almost 2 years ago
  • model-00001-of-00002.safetensors
    5 GB
    xet
    '优化模型量化损失' almost 2 years ago
  • model-00002-of-00002.safetensors
    1.89 GB
    xet
    '优化模型量化损失' almost 2 years ago
  • model.safetensors.index.json
    89.5 kB
    'decrease gptq group size' almost 2 years ago
  • modeling_chatglm.py
    53 kB
    '优化模型量化损失' almost 2 years ago
  • special_tokens_map.json
    601 Bytes
    'upload model' almost 2 years ago
  • tokenization_chatglm.py
    15.6 kB
    'upload model' almost 2 years ago
  • tokenizer.model
    2.62 MB
    xet
    'upload model' almost 2 years ago
  • tokenizer_config.json
    3.2 kB
    'upload model' almost 2 years ago