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Lyon28
/
caca-650M-untrained

Text Generation
Transformers
Safetensors
PyTorch
Indonesian
English
caca
causal-lm
transformer
untrained
mla
multi-token-prediction
qk-norm
rope
yarn
swiglu
rmsnorm
sliding-window-attention
indonesian
bilingual
custom_code
Model card Files Files and versions
xet
Community

Instructions to use Lyon28/caca-650M-untrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Lyon28/caca-650M-untrained with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="Lyon28/caca-650M-untrained", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("Lyon28/caca-650M-untrained", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use Lyon28/caca-650M-untrained with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "Lyon28/caca-650M-untrained"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "Lyon28/caca-650M-untrained",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/Lyon28/caca-650M-untrained
  • SGLang

    How to use Lyon28/caca-650M-untrained 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 "Lyon28/caca-650M-untrained" \
        --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": "Lyon28/caca-650M-untrained",
    		"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 "Lyon28/caca-650M-untrained" \
            --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": "Lyon28/caca-650M-untrained",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use Lyon28/caca-650M-untrained with Docker Model Runner:

    docker model run hf.co/Lyon28/caca-650M-untrained
caca-650M-untrained
1.05 GB
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  • 1 contributor
History: 7 commits
Lyon28's picture
Lyon28
Upload README.md with huggingface_hub
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  • .gitattributes
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    initial commit 22 days ago
  • README.md
    9.17 kB
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  • config.json
    1.88 kB
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  • configuration_caca.py
    4.42 kB
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  • generation_config.json
    216 Bytes
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  • model.safetensors
    1.05 GB
    xet
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  • modeling_caca.py
    22.6 kB
    Upload modeling_caca.py with huggingface_hub 22 days ago