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Duplicated from  zai-org/chatglm-6b-int4

NewBreaker
/
chatglm-6b-int4

Text Generation
Transformers
PyTorch
English
chatglm
conversational
text2text-generation
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use NewBreaker/chatglm-6b-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NewBreaker/chatglm-6b-int4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="NewBreaker/chatglm-6b-int4", trust_remote_code=True)
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("NewBreaker/chatglm-6b-int4", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use NewBreaker/chatglm-6b-int4 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "NewBreaker/chatglm-6b-int4"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "NewBreaker/chatglm-6b-int4",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/NewBreaker/chatglm-6b-int4
  • SGLang

    How to use NewBreaker/chatglm-6b-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 "NewBreaker/chatglm-6b-int4" \
        --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": "NewBreaker/chatglm-6b-int4",
    		"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 "NewBreaker/chatglm-6b-int4" \
            --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": "NewBreaker/chatglm-6b-int4",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use NewBreaker/chatglm-6b-int4 with Docker Model Runner:

    docker model run hf.co/NewBreaker/chatglm-6b-int4
chatglm-6b-int4
8.87 GB
Ctrl+K
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  • 3 contributors
History: 39 commits
NewBreaker
auto git
a72ec88 about 3 years ago
  • .idea
    first about 3 years ago
  • models
    auto git about 3 years ago
  • .gitattributes
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  • LICENSE
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  • MODEL_LICENSE
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  • README.md
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  • config.json
    843 Bytes
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  • configuration_chatglm.py
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  • demo_api.py
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  • demo_call_api.py
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  • demo_call_cpu_model.py
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  • demo_convert_2_cpu.py
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  • demo_pipeline.py
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  • demo_update_config.py
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  • ice_text.model
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  • load_model.py
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  • modeling_chatglm.py
    59.4 kB
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.HalfStorage",
    • "torch.CharStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict"

    What is a pickle import?

    3.89 GB
    xet
    five about 3 years ago
  • quantization.py
    30.8 kB
    auto git about 3 years ago
  • tokenization_chatglm.py
    16.7 kB
    five about 3 years ago
  • tokenizer_config.json
    451 Bytes
    add questions all about 3 years ago