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c-bone
/
CrystaLLM-pi_base

Text Generation
Transformers
Safetensors
English
gpt2
materials-science
crystallography
generative-ai
inverse-design
chemistry
unconditional
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use c-bone/CrystaLLM-pi_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use c-bone/CrystaLLM-pi_base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="c-bone/CrystaLLM-pi_base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("c-bone/CrystaLLM-pi_base")
    model = AutoModelForCausalLM.from_pretrained("c-bone/CrystaLLM-pi_base")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use c-bone/CrystaLLM-pi_base with vLLM:

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

    How to use c-bone/CrystaLLM-pi_base 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 "c-bone/CrystaLLM-pi_base" \
        --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": "c-bone/CrystaLLM-pi_base",
    		"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 "c-bone/CrystaLLM-pi_base" \
            --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": "c-bone/CrystaLLM-pi_base",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use c-bone/CrystaLLM-pi_base with Docker Model Runner:

    docker model run hf.co/c-bone/CrystaLLM-pi_base
CrystaLLM-pi_base
104 MB
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  • 1 contributor
History: 3 commits
c-bone's picture
c-bone
Create README.md
6eb8584 verified 5 months ago
  • .gitattributes
    1.52 kB
    initial commit 7 months ago
  • README.md
    4.44 kB
    Create README.md 5 months ago
  • config.json
    766 Bytes
    Upload base model checkpoint 7 months ago
  • model.safetensors
    104 MB
    xet
    Upload base model checkpoint 7 months ago
  • tokenizer_config.json
    82 Bytes
    Upload base model checkpoint 7 months ago