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Veer15
/
bloomz-3b-4bit-quant

Text Generation
PEFT
PyTorch
English
bloom
4-bit precision
gptq
Model card Files Files and versions
xet
Community

Instructions to use Veer15/bloomz-3b-4bit-quant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use Veer15/bloomz-3b-4bit-quant with PEFT:

    Task type is invalid.
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Veer15/bloomz-3b-4bit-quant with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Veer15/bloomz-3b-4bit-quant"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Veer15/bloomz-3b-4bit-quant",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Veer15/bloomz-3b-4bit-quant
  • SGLang

    How to use Veer15/bloomz-3b-4bit-quant 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 "Veer15/bloomz-3b-4bit-quant" \
        --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": "Veer15/bloomz-3b-4bit-quant",
    		"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 "Veer15/bloomz-3b-4bit-quant" \
            --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": "Veer15/bloomz-3b-4bit-quant",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Veer15/bloomz-3b-4bit-quant with Docker Model Runner:

    docker model run hf.co/Veer15/bloomz-3b-4bit-quant
bloomz-3b-4bit-quant
2.53 GB
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  • 1 contributor
History: 7 commits
Veer15's picture
Veer15
Update README.md
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  • README.md
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  • config.json
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  • generation_config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    2.51 GB
    xet
    Upload BloomForCausalLM over 2 years ago
  • special_tokens_map.json
    96 Bytes
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  • tokenizer.json
    14.5 MB
    xet
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    260 Bytes
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