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opencerebral
/
littlerock-1M-arithmax

Text Generation
Transformers
Safetensors
English
llama
small-language-model
research-artifact
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use opencerebral/littlerock-1M-arithmax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use opencerebral/littlerock-1M-arithmax with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="opencerebral/littlerock-1M-arithmax")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("opencerebral/littlerock-1M-arithmax")
    model = AutoModelForCausalLM.from_pretrained("opencerebral/littlerock-1M-arithmax", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use opencerebral/littlerock-1M-arithmax with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "opencerebral/littlerock-1M-arithmax"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "opencerebral/littlerock-1M-arithmax",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/opencerebral/littlerock-1M-arithmax
  • SGLang

    How to use opencerebral/littlerock-1M-arithmax 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 "opencerebral/littlerock-1M-arithmax" \
        --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": "opencerebral/littlerock-1M-arithmax",
    		"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 "opencerebral/littlerock-1M-arithmax" \
            --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": "opencerebral/littlerock-1M-arithmax",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use opencerebral/littlerock-1M-arithmax with Docker Model Runner:

    docker model run hf.co/opencerebral/littlerock-1M-arithmax
littlerock-1M-arithmax
4.29 MB
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  • 1 contributor
History: 3 commits
KlondikeDev's picture
KlondikeDev
Reframe: narrow generalization, not misconduct
212ec41 verified 2 months ago
  • .gitattributes
    1.52 kB
    initial commit 2 months ago
  • README.md
    4.92 kB
    Reframe: narrow generalization, not misconduct 2 months ago
  • config.json
    627 Bytes
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago
  • generation_config.json
    86 Bytes
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago
  • littlerock_config.json
    1.65 kB
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago
  • model.safetensors
    4.02 MB
    xet
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago
  • special_tokens_map.json
    98 Bytes
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago
  • tokenizer.json
    263 kB
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago
  • tokenizer_config.json
    442 Bytes
    littlerock-1M-arithmax: documented benchmark-specialization case 2 months ago