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zai-org
/
cogagent-9b-20241220

Image-Text-to-Text
Transformers
Safetensors
Chinese
English
chatglm
feature-extraction
custom_code
Model card Files Files and versions
xet
Community

Instructions to use zai-org/cogagent-9b-20241220 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use zai-org/cogagent-9b-20241220 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="zai-org/cogagent-9b-20241220", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("zai-org/cogagent-9b-20241220", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use zai-org/cogagent-9b-20241220 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "zai-org/cogagent-9b-20241220"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "zai-org/cogagent-9b-20241220",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/zai-org/cogagent-9b-20241220
  • SGLang

    How to use zai-org/cogagent-9b-20241220 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 "zai-org/cogagent-9b-20241220" \
        --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": "zai-org/cogagent-9b-20241220",
    		"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 "zai-org/cogagent-9b-20241220" \
            --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": "zai-org/cogagent-9b-20241220",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use zai-org/cogagent-9b-20241220 with Docker Model Runner:

    docker model run hf.co/zai-org/cogagent-9b-20241220
cogagent-9b-20241220
27.8 GB
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  • 3 contributors
History: 7 commits
zR
finish
0de2cad over 1 year ago
  • .gitattributes
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  • LICENSE
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  • README.md
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  • README_zh.md
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  • config.json
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  • configuration_chatglm.py
    2.57 kB
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  • generation_config.json
    211 Bytes
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  • model-00001-of-00006.safetensors
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  • model-00002-of-00006.safetensors
    4.9 GB
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  • model-00003-of-00006.safetensors
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  • model-00004-of-00006.safetensors
    4.95 GB
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  • model-00005-of-00006.safetensors
    4.97 GB
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  • model-00006-of-00006.safetensors
    3.12 GB
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  • model.safetensors.index.json
    111 kB
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  • modeling_chatglm.py
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  • tokenization_chatglm.py
    14.5 kB
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  • tokenizer.model
    2.62 MB
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  • tokenizer_config.json
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  • visual.py
    6.87 kB
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